Title:
Probabilità Un’introduzione attraverso modelli e applicazioni / by Francesco Caravenna, Paolo Dai Pra.
UNITEXT,
UNITEXT,
Author:
Caravenna, Francesco. author.
Dai Pra, Paolo. author.
SpringerLink (Online service)
General Notes:
Spazi di probabilità discreti: teoria -- Spazi di probabilità discreti: esempi e applicazioni -- Variabili aleatorie discrete: teoria -- Variabili aleatorie discrete: esempi e applicazioni -- Spazi di probabilità e variabili aleatorie generali -- Variabili aleatorie assolutamente continue -- Teoremi limite -- Applicazioni alla statistica matematica -- Appendice -- Tavola della distribuzione normale -- Principali distribuzioni notevoli su R.
Il presente volume intende fornire un’introduzione alla probabilità e alle sue applicazioni, senza fare ricorso alla teoria della misura, per studenti dei corsi di laurea scientifici (in particolar modo di matematica, fisica e ingegneria). Viene dedicato ampio spazio alla probabilità discreta, vale a dire su spazi finiti o numerabili. In questo contesto sono sufficienti pochi strumenti analitici per presentare la teoria in modo completo e rigoroso. L'esposizione è arricchita dall'analisi dettagliata di diversi modelli, di facile formulazione e allo stesso tempo di grande rilevanza teorica e applicativa, alcuni tuttora oggetto di ricerca. Vengono poi trattate le variabili aleatorie assolutamente continue, reali e multivariate, e i teoremi limite classici della probabilità, ossia la Legge dei Grandi Numeri e il Teorema Limite Centrale, dando rilievo tanto agli aspetti concettuali quanto a quelli applicativi. Tra le varie applicazioni presentate, un capitolo è dedicato alla stima dei parametri in Statistica Matematica. Numerosi esempi sono parte integrante dell'esposizione. Ogni capitolo contiene una ricca selezione di esercizi, per i quali viene fornita la soluzione sul sito Springer dedicato al volume.
Publisher:
Springer Milan : Imprint: Springer,
Publication Place:
Milano :
ISBN:
9788847025950
Subject:
Mathematics.
Distribution (Probability theory).
Statistics.
Mathematics.
Probability Theory and Stochastic Processes.
Statistics, general.
Series:
UNITEXT, 67
UNITEXT, 67
Contents:
Spazi di probabilità discreti: teoria -- Spazi di probabilità discreti: esempi e applicazioni -- Variabili aleatorie discrete: teoria -- Variabili aleatorie discrete: esempi e applicazioni -- Spazi di probabilità e variabili aleatorie generali -- Variabili aleatorie assolutamente continue -- Teoremi limite -- Applicazioni alla statistica matematica -- Appendice -- Tavola della distribuzione normale -- Principali distribuzioni notevoli su R.
Physical Description:
X, 403 pagg. online resource.
Electronic Location:
http://dx.doi.org/10.1007/978-88-470-2595-0
Publication Date:
2013.
Title:
Probabilités et processus stochastiques by Yves Caumel.
Statistique et probabilités appliquées
Statistique et probabilités appliquées
Author:
Caumel, Yves.
SpringerLink (Online service)
General Notes:
<p>Ce livre a pour objectif de fournir au lecteur les bases théoriques nécessaires à la maîtrise des concepts et des méthodes utilisées en théorie des probabilités, telle qu’elle s’est développée au dix-septième siècle par l’étude des jeux de hasard, pour aboutir aujourd’hui à la théorisation de phénomènes aussi complexes et différents que les processus de diffusion en physique ou l’évolution des marchés financiers.</p><p>Après un exposé introductif à la théorie probabiliste dont les liens avec l’analyse fonctionnelle et harmonique sont soulignés, l’auteur présente en détail une sélection de processus aléatoires classiques de type markoviens à temps entiers et continus, poissoniens, stationnaires,etc., et leurs diverses applications dans des contextes tels que le traitement du signal, la gestion des stocks,la modélisation des files d’attente, et d’autres encore. Le livre se conclut par une présentation détaillée du mouvement brownien et de sa genèse.</p><p>Cent cinquante exercices (pour la plupart corrigés), ainsi qu’un ensemble de notules historiques ou épistémologiques permettant d’illustrer la dynamique et le contexte de découverte des théories évoquées, viennent compléter cet ouvrage. Celui-ci sera particulièrement adapté aux élèves ingénieurs ainsi qu’aux étudiants des 1er et 2e cycles universitaires dans des disciplines aussi variées que les mathématiques, la physique, l’automatique, l’économie et la gestion.</p>
Publisher:
Springer Paris,
Publication Place:
Paris :
ISBN:
9782817801636
Subject:
Statistics.
Statistics.
Statistics, general.
Series:
Statistique et probabilités appliquées
Statistique et probabilités appliquées
Physical Description:
XII, 304p. digital.
Electronic Location:
http://dx.doi.org/10.1007/978-2-8178-0163-6
Publication Date:
2011.
Title:
Probabilities, Causes and Propensities in Physics edited by Mauricio Suárez.
Synthese Library, Studies in Epistemology, Logic, Methodology, and Philosophy of Science ;
Synthese Library, Studies in Epistemology, Logic, Methodology, and Philosophy of Science ;
Author:
Suárez, Mauricio.
SpringerLink (Online service)
General Notes:
Preface -- 1. Introduction; Mauricio Suárez -- PART I: PROBABILITIES -- 2. Probability and time symmetry in classical Markov processes; Guido Bacciagaluppi -- 3. Probability assignments and the principle of indifference: An examination of two eliminative strategies; Sorin Bangu -- 4. Why typicality does not explain the approach to equilibrium; Roman Frigg; PART II: CAUSES -- 5. From metaphysics to physics and back: The example of causation; Federico Laudisa -- 6. On explanation in retro-causal interpretations of quantum mechanics; Joseph Berkovitz -- 7. Causal completeness in general probability theories; Balasz Gyenis, Miklós Rédei -- 8. Causal Markov, robustness and the quantum correlations; Mauricio Suárez, Iñaki San Pedro -- PART III: PROPENSITIES -- 9. Do dispositions and propensities have a role in the ontology of quantum mechanics? Some critical remarks; Mauro Dorato -- 10. Is the quantum world composed of propensitons?; Nicholas Maxwell -- 11. Derivative dispositions and multiple derivative levels; Ian Thompson.
This volume defends a novel approach to the philosophy of physics: it is the first book devoted to a comparative study of probability, causality, and propensity, and their various interrelations, within the context of contemporary physics -- particularly quantum and statistical physics. The philosophical debates and distinctions are firmly grounded upon examples from actual physics, thus exemplifying a robustly empiricist approach. The essays, by both prominent scholars in the field and promising young researchers, constitute a pioneer effort in bringing out the connections between probabilistic, causal and dispositional aspects of the quantum domain. The book will appeal to specialists in philosophy and foundations of physics, philosophy of science in general, metaphysics, ontology of physics theories, and philosophy of probability.
Publisher:
Springer Netherlands,
Publication Place:
Dordrecht :
ISBN:
9781402099045
Subject:
Philosophy (General).
Metaphysics.
Science -- Philosophy.
Quantum theory.
Philosophy.
Philosophy of Science.
Metaphysics.
Quantum physics.
Statistical Physics, Dynamical Systems and Complexity.
Series:
Synthese Library, Studies in Epistemology, Logic, Methodology, and Philosophy of Science ; 347
Synthese Library, Studies in Epistemology, Logic, Methodology, and Philosophy of Science ; 347
Contents:
Preface -- 1. Introduction; Mauricio Suárez -- PART I: PROBABILITIES -- 2. Probability and time symmetry in classical Markov processes; Guido Bacciagaluppi -- 3. Probability assignments and the principle of indifference: An examination of two eliminative strategies; Sorin Bangu -- 4. Why typicality does not explain the approach to equilibrium; Roman Frigg; PART II: CAUSES -- 5. From metaphysics to physics and back: The example of causation; Federico Laudisa -- 6. On explanation in retro-causal interpretations of quantum mechanics; Joseph Berkovitz -- 7. Causal completeness in general probability theories; Balasz Gyenis, Miklós Rédei -- 8. Causal Markov, robustness and the quantum correlations; Mauricio Suárez, Iñaki San Pedro -- PART III: PROPENSITIES -- 9. Do dispositions and propensities have a role in the ontology of quantum mechanics? Some critical remarks; Mauro Dorato -- 10. Is the quantum world composed of propensitons?; Nicholas Maxwell -- 11. Derivative dispositions and multiple derivative levels; Ian Thompson.
Physical Description:
X, 266 p. digital.
Electronic Location:
http://dx.doi.org/10.1007/978-1-4020-9904-5
Publication Date:
2011.
There are no items available
Title:
Probabilities, Laws, and Structures edited by Dennis Dieks, Wenceslao J. Gonzalez, Stephan Hartmann, Michael Stöltzner, Marcel Weber.
The Philosophy of Science in a European Perspective ;
The Philosophy of Science in a European Perspective ;
Author:
Dieks, Dennis. editor.
Gonzalez, Wenceslao J. editor.
Hartmann, Stephan. editor.
Stöltzner, Michael. editor.
Weber, Marcel. editor.
SpringerLink (Online service)
General Notes:
MARCEL WEBER, Preface.- Team A: Formal Methods SEAMUS BRADLEY, Dutch Book Arguments and Imprecise Probabilities.-TIMOTHY CHILDERS, Objectifying Subjective Probabilities: Dutch Book Arguments for Principles of Direct Inference.- ILKKA NIINILUOTO, The Foundations of Statistics: Inference vs. Decision -- ROBERTO FESTA, On the Verisimilitude of Tendency Hypotheses.-GERHARD SCHURZ, Tweety, or Why Probabilism and even Bayesianism Need Objective and Evidential Probabilities.-DAVID ATKINSON AND JEANNE PEIJNENBURG, Pluralism in Probabilistic Justification.- JAN-WILLEM ROMEIJN, RENS VAN DE SCHOOT, HERBERT HOIJTINK, One Size Does not Fit All: Proposal for a Prior-adapted BIC.- Team B: Philosophy of the Natural and Life Sciences Team D: Philosophy of the Physical Sciences.-MAURO DORATO, Mathematical Biology and the Existence of Biological Laws.-FEDERICA RUSSO, On Empirical Generalisations.-SEBASTIAN MATEIESCU, The Limits of Interventionism – Causality in the Social Sciences.-MICHAEL ESFELD, Causal Realism.-HOLGER LYRE, Structural Invariants, Structural Kinds, Structural Laws.-PAUL HOYNINGEN-HUENE, Santa's Gift of Structural Realism.-STEVEN FRENCH, The Resilience of Laws and the Ephemerality of Objects: Can a Form of Structuralism be Extended to Biology? -- MICHELA MASSIMI, Natural Kinds, Conceptual Change, and the Duck-bill Platypus: LaPorte on Incommensurability.-THOMAS A. C. REYDON, Essentialism about Kinds: An Undead Issue in the Philosophies of Physics and Biology?.-CHRISTIAN SACHSE, Biological Laws and Kinds within a Conservative Reductionist Framework.-ARIE I. KAISER, Why It Is Time to Move beyond Nagelian Reduction.-CHARLOTTE WERNDL, Probability, Indeterminism and Biological Processes.-BENGT AUTZEN, Bayesianism, Convergence and Molecular Phylogenetics -- Team C: Philosophy of the Cultural and Social Sciences.-ILKKA NIINILUOTO, Quantities as Realistic Idealizations.-MARCEL BOUMANS, Mathematics as Quasi-matter to Build Models as Instruments.-DAVID F. HENDRY, Mathematical Models and Economic Forecasting: Some Uses and Mis-Uses of Mathematics in Economics.-JAVIER ECHEVERRIA, Technomathematical Models in the Social Sciences.-DONALD GILLIES, The Use of Mathematics in Physics and Economics: A Comparison.-DANIEL ANDLER, Mathematics in Cognitive Science.-LADISLAV KVASZ, What Can the Social Sciences Learn from the Process of Mathematization in the Natural Sciences.-MARIA CARLA GALAVOTTI, Probability, Statistics, and Law.-ADRIAN MIROIU, Experiments in Political Science: The Case of the Voting Rules -- Team E: History of the Philosophy of Science VOLKER PECKHAUS, The Beginning of Model Theory in the Algebra of Logic.-GRAHAM STEVENS, Incomplete Symbols and the Theory of Logical Types.-DONATA ROMIZI, Statistical Thinking between Natural and Social Sciences and the Issue of the Unity of Science: From Quetelet to the Vienna Circle.-ARTUR KOTERSKI, The Backbone of the Straw Man. Popper’s Critique of the Vienna Circle’s Inductivism.-THOMAS UEBEL, Carnap’s Logic of Science and Personal Probability.-MICHAEL STÖLTZNER, Erwin Schrödinger, Vienna Indeterminist.-MIKLOS REDEI, Some Historical and Philosophical Aspects of Quantum Probability Theory and its Interpretation.-INDEX OF NAMES. SEAMUS BRADLEY, Dutch Book Arguments and Imprecise Probabilities.-TIMOTHY CHILDERS, Objectifying Subjective Probabilities: Dutch Book Arguments for Principles of Direct Inference.- ILKKA NIINILUOTO, The Foundations of Statistics: Inference vs. Decision -- ROBERTO FESTA, On the Verisimilitude of Tendency Hypotheses.-GERHARD SCHURZ, Tweety, or Why Probabilism and even Bayesianism Need Objective and Evidential Probabilities.-DAVID ATKINSON AND JEANNE PEIJNENBURG, Pluralism in Probabilistic Justification.- JAN-WILLEM ROMEIJN, RENS VAN DE SCHOOT, HERBERT HOIJTINK, One Size Does not Fit All: Proposal for a Prior-adapted BIC.- Team B: Philosophy of the Natural and Life Sciences Team D: Philosophy of the Physical Sciences.-MAURO DORATO, Mathematical Biology and the Existence of Biological Laws.-FEDERICA RUSSO, On Empirical Generalisations.-SEBASTIAN MATEIESCU, The Limits of Interventionism – Causality in the Social Sciences.-MICHAEL ESFELD, Causal Realism.-HOLGER LYRE, Structural Invariants, Structural Kinds, Structural Laws.-PAUL HOYNINGEN-HUENE, Santa's Gift of Structural Realism.-STEVEN FRENCH, The Resilience of Laws and the Ephemerality of Objects: Can a Form of Structuralism be Extended to Biology? -- MICHELA MASSIMI, Natural Kinds, Conceptual Change, and the Duck-bill Platypus: LaPorte on Incommensurability.-THOMAS A. C. REYDON, Essentialism about Kinds: An Undead Issue in the Philosophies of Physics and Biology?.-CHRISTIAN SACHSE, Biological Laws and Kinds within a Conservative Reductionist Framework.-ARIE I. KAISER, Why It Is Time to Move beyond Nagelian Reduction.-CHARLOTTE WERNDL, Probability, Indeterminism and Biological Processes.-BENGT AUTZEN, Bayesianism, Convergence and Molecular Phylogenetics -- Team C: Philosophy of the Cultural and Social Sciences.-ILKKA NIINILUOTO, Quantities as Realistic Idealizations.-MARCEL BOUMANS, Mathematics as Quasi-matter to Build Models as Instruments.-DAVID F. HENDRY, Mathematical Models and Economic Forecasting: Some Uses and Mis-Uses of Mathematics in Economics.-JAVIER ECHEVERRIA, Technomathematical Models in the Social Sciences.-DONALD GILLIES, The Use of Mathematics in Physics and Economics: A Comparison.-DANIEL ANDLER, Mathematics in Cognitive Science.-LADISLAV KVASZ, What Can the Social Sciences Learn from the Process of Mathematization in the Natural Sciences.-MARIA CARLA GALAVOTTI, Probability, Statistics, and Law.-ADRIAN MIROIU, Experiments in Political Science: The Case of the Voting Rules -- Team E: History of the Philosophy of Science VOLKER PECKHAUS, The Beginning of Model Theory in the Algebra of Logic.-GRAHAM STEVENS, Incomplete Symbols and the Theory of Logical Types.-DONATA ROMIZI, Statistical Thinking between Natural and Social Sciences and the Issue of the Unity of Science: From Quetelet to the Vienna Circle.-ARTUR KOTERSKI, The Backbone of the Straw Man. Popper’s Critique of the Vienna Circle’s Inductivism.-THOMAS UEBEL, Carnap’s Logic of Science and Personal Probability.-MICHAEL STÖLTZNER, Erwin Schrödinger, Vienna Indeterminist.-MIKLOS REDEI, Some Historical and Philosophical Aspects of Quantum Probability Theory and its Interpretation.-INDEX OF NAMES. .
This volume, the third in this Springer series, contains selected papers from the four workshops organized by the ESF Research Networking Programme "The Philosophy of Science in a European Perspective" (PSE) in 2010: Pluralism in the Foundations of Statistics Points of Contact between the Philosophy of Physics and the Philosophy of Biology The Debate on Mathematical Modeling in the Social Sciences Historical Debates about Logic, Probability and Statistics The volume is accordingly divided in four sections, each of them containing papers coming from the workshop focussing on one of these themes. While the programme's core topic for the year 2010 was probability and statistics, the organizers of the workshops embraced the opportunity of building bridges to more or less closely connected issues in general philosophy of science, philosophy of physics and philosophy of the special sciences. However, papers that analyze the concept of probability for various philosophical purposes are clearly a major theme in this volume, as it was in the previous volumes of the same series. This reflects the impressive productivity of probabilistic approaches in the philosophy of science, which form an important part of what has become known as formal epistemology - although, of course, there are non-probabilistic approaches in formal epistemology as well. It is probably fair to say that Europe has been particularly strong in this area of philosophy in recent years.
Publisher:
Springer Netherlands,
Publication Place:
Dordrecht :
ISBN:
9789400730304
Subject:
Philosophy (General).
Genetic epistemology.
Biology -- Philosophy.
Science -- Philosophy.
Social sciences -- Philosophy.
Philosophy.
Philosophy of Science.
Philosophy of the Social Sciences.
Philosophy of Biology.
Epistemology.
Series:
The Philosophy of Science in a European Perspective ; 3
The Philosophy of Science in a European Perspective ; 3
Contents:
MARCEL WEBER, Preface.- Team A: Formal Methods SEAMUS BRADLEY, Dutch Book Arguments and Imprecise Probabilities.-TIMOTHY CHILDERS, Objectifying Subjective Probabilities: Dutch Book Arguments for Principles of Direct Inference.- ILKKA NIINILUOTO, The Foundations of Statistics: Inference vs. Decision -- ROBERTO FESTA, On the Verisimilitude of Tendency Hypotheses.-GERHARD SCHURZ, Tweety, or Why Probabilism and even Bayesianism Need Objective and Evidential Probabilities.-DAVID ATKINSON AND JEANNE PEIJNENBURG, Pluralism in Probabilistic Justification.- JAN-WILLEM ROMEIJN, RENS VAN DE SCHOOT, HERBERT HOIJTINK, One Size Does not Fit All: Proposal for a Prior-adapted BIC.- Team B: Philosophy of the Natural and Life Sciences Team D: Philosophy of the Physical Sciences.-MAURO DORATO, Mathematical Biology and the Existence of Biological Laws.-FEDERICA RUSSO, On Empirical Generalisations.-SEBASTIAN MATEIESCU, The Limits of Interventionism – Causality in the Social Sciences.-MICHAEL ESFELD, Causal Realism.-HOLGER LYRE, Structural Invariants, Structural Kinds, Structural Laws.-PAUL HOYNINGEN-HUENE, Santa's Gift of Structural Realism.-STEVEN FRENCH, The Resilience of Laws and the Ephemerality of Objects: Can a Form of Structuralism be Extended to Biology? -- MICHELA MASSIMI, Natural Kinds, Conceptual Change, and the Duck-bill Platypus: LaPorte on Incommensurability.-THOMAS A. C. REYDON, Essentialism about Kinds: An Undead Issue in the Philosophies of Physics and Biology?.-CHRISTIAN SACHSE, Biological Laws and Kinds within a Conservative Reductionist Framework.-ARIE I. KAISER, Why It Is Time to Move beyond Nagelian Reduction.-CHARLOTTE WERNDL, Probability, Indeterminism and Biological Processes.-BENGT AUTZEN, Bayesianism, Convergence and Molecular Phylogenetics -- Team C: Philosophy of the Cultural and Social Sciences.-ILKKA NIINILUOTO, Quantities as Realistic Idealizations.-MARCEL BOUMANS, Mathematics as Quasi-matter to Build Models as Instruments.-DAVID F. HENDRY, Mathematical Models and Economic Forecasting: Some Uses and Mis-Uses of Mathematics in Economics.-JAVIER ECHEVERRIA, Technomathematical Models in the Social Sciences.-DONALD GILLIES, The Use of Mathematics in Physics and Economics: A Comparison.-DANIEL ANDLER, Mathematics in Cognitive Science.-LADISLAV KVASZ, What Can the Social Sciences Learn from the Process of Mathematization in the Natural Sciences.-MARIA CARLA GALAVOTTI, Probability, Statistics, and Law.-ADRIAN MIROIU, Experiments in Political Science: The Case of the Voting Rules -- Team E: History of the Philosophy of Science VOLKER PECKHAUS, The Beginning of Model Theory in the Algebra of Logic.-GRAHAM STEVENS, Incomplete Symbols and the Theory of Logical Types.-DONATA ROMIZI, Statistical Thinking between Natural and Social Sciences and the Issue of the Unity of Science: From Quetelet to the Vienna Circle.-ARTUR KOTERSKI, The Backbone of the Straw Man. Popper’s Critique of the Vienna Circle’s Inductivism.-THOMAS UEBEL, Carnap’s Logic of Science and Personal Probability.-MICHAEL STÖLTZNER, Erwin Schrödinger, Vienna Indeterminist.-MIKLOS REDEI, Some Historical and Philosophical Aspects of Quantum Probability Theory and its Interpretation.-INDEX OF NAMES. SEAMUS BRADLEY, Dutch Book Arguments and Imprecise Probabilities.-TIMOTHY CHILDERS, Objectifying Subjective Probabilities: Dutch Book Arguments for Principles of Direct Inference.- ILKKA NIINILUOTO, The Foundations of Statistics: Inference vs. Decision -- ROBERTO FESTA, On the Verisimilitude of Tendency Hypotheses.-GERHARD SCHURZ, Tweety, or Why Probabilism and even Bayesianism Need Objective and Evidential Probabilities.-DAVID ATKINSON AND JEANNE PEIJNENBURG, Pluralism in Probabilistic Justification.- JAN-WILLEM ROMEIJN, RENS VAN DE SCHOOT, HERBERT HOIJTINK, One Size Does not Fit All: Proposal for a Prior-adapted BIC.- Team B: Philosophy of the Natural and Life Sciences Team D: Philosophy of the Physical Sciences.-MAURO DORATO, Mathematical Biology and the Existence of Biological Laws.-FEDERICA RUSSO, On Empirical Generalisations.-SEBASTIAN MATEIESCU, The Limits of Interventionism – Causality in the Social Sciences.-MICHAEL ESFELD, Causal Realism.-HOLGER LYRE, Structural Invariants, Structural Kinds, Structural Laws.-PAUL HOYNINGEN-HUENE, Santa's Gift of Structural Realism.-STEVEN FRENCH, The Resilience of Laws and the Ephemerality of Objects: Can a Form of Structuralism be Extended to Biology? -- MICHELA MASSIMI, Natural Kinds, Conceptual Change, and the Duck-bill Platypus: LaPorte on Incommensurability.-THOMAS A. C. REYDON, Essentialism about Kinds: An Undead Issue in the Philosophies of Physics and Biology?.-CHRISTIAN SACHSE, Biological Laws and Kinds within a Conservative Reductionist Framework.-ARIE I. KAISER, Why It Is Time to Move beyond Nagelian Reduction.-CHARLOTTE WERNDL, Probability, Indeterminism and Biological Processes.-BENGT AUTZEN, Bayesianism, Convergence and Molecular Phylogenetics -- Team C: Philosophy of the Cultural and Social Sciences.-ILKKA NIINILUOTO, Quantities as Realistic Idealizations.-MARCEL BOUMANS, Mathematics as Quasi-matter to Build Models as Instruments.-DAVID F. HENDRY, Mathematical Models and Economic Forecasting: Some Uses and Mis-Uses of Mathematics in Economics.-JAVIER ECHEVERRIA, Technomathematical Models in the Social Sciences.-DONALD GILLIES, The Use of Mathematics in Physics and Economics: A Comparison.-DANIEL ANDLER, Mathematics in Cognitive Science.-LADISLAV KVASZ, What Can the Social Sciences Learn from the Process of Mathematization in the Natural Sciences.-MARIA CARLA GALAVOTTI, Probability, Statistics, and Law.-ADRIAN MIROIU, Experiments in Political Science: The Case of the Voting Rules -- Team E: History of the Philosophy of Science VOLKER PECKHAUS, The Beginning of Model Theory in the Algebra of Logic.-GRAHAM STEVENS, Incomplete Symbols and the Theory of Logical Types.-DONATA ROMIZI, Statistical Thinking between Natural and Social Sciences and the Issue of the Unity of Science: From Quetelet to the Vienna Circle.-ARTUR KOTERSKI, The Backbone of the Straw Man. Popper’s Critique of the Vienna Circle’s Inductivism.-THOMAS UEBEL, Carnap’s Logic of Science and Personal Probability.-MICHAEL STÖLTZNER, Erwin Schrödinger, Vienna Indeterminist.-MIKLOS REDEI, Some Historical and Philosophical Aspects of Quantum Probability Theory and its Interpretation.-INDEX OF NAMES. .
Physical Description:
XI, 512p. 15 illus. online resource.
Electronic Location:
http://dx.doi.org/10.1007/978-94-007-3030-4
Publication Date:
2012.
Title:
Probability : a graduate course / Allan Gut.
Springer texts in statistics,
Springer texts in statistics.
Author:
Gut, Allan, 1944-, author.
General Notes:
Includes bibliographical references (pages 577-586) and index.
Introductory measure theory -- Random variables -- Inequalities -- Characteristic functions -- Convergence -- Law of large numbers -- Central limit theorem -- Law of the iterated logarithm -- Limit theorems: Extensions and generalizations -- Martingales -- Appendix: Some useful mathematics.
Publisher:
Springer,
Publication Place:
New York :
ISBN:
9781461447078
1461447070
1489997555
9781489997555
9781461447085
Subject:
Probabilities.
Distribution (Probability theory)
Probabilistic number theory.
Series:
Springer texts in statistics,
Springer texts in statistics.
Edition:
Second edition.
Contents:
Introductory measure theory -- Random variables -- Inequalities -- Characteristic functions -- Convergence -- Law of large numbers -- Central limit theorem -- Law of the iterated logarithm -- Limit theorems: Extensions and generalizations -- Martingales -- Appendix: Some useful mathematics.
Physical Description:
xxv, 600 pages ;
Publication Date:
[2013]
Title:
Probability & statistics for engineers & scientists / Ronald E. Walpole [and others]. Probability and statistics for engineers and scientists
Probability and statistics for engineers and scientists Probability and statistics for engineers and scientists
Author:
Walpole, Ronald E.
General Notes:
Includes bibliographical references (pages 737-740) and index.
1. Introduction to statistics and data analysis -- 2. Probability -- 3. Random variables and probability distributions -- 4. Mathematical expectation -- 5. Some discrete probability distributions -- 6. Some continuous probability distributions -- 7. Functions of random variables (optional) -- 8. Fundamental sampling distributions and data descriptions -- 9. One- and two-sample estimation problems -- 10. One- and two-sample tests of hypotheses -- 11. Simple linear regression and correlation -- 12. Multiple linear regression and certain nonlinear regression models -- 13. One-factor experiments : general -- 14. Factorial experiments (two or more factors) -- 15. 2[superscript k] factorial experiments and fractions.
Publisher:
Pearson Prentice Hall,
Publication Place:
Upper Saddle River, NJ :
ISBN:
9780131877115
0131877119
9780132047678
0132047675
Subject:
Engineering. -- Statistical methods.
Probabilities.
Edition:
Eighth Edition.
Contents:
Introduction to statistics and data analysis -- Probability -- Random variables and probability distributions -- Mathematical expectation -- Some discrete probability distributions -- Some continuous probability distributions -- Functions of random variables (optional) -- Fundamental sampling distributions and data descriptions -- One- and two-sample estimation problems -- One- and two-sample tests of hypotheses -- Simple linear regression and correlation -- Multiple linear regression and certain nonlinear regression models -- One-factor experiments : general -- Factorial experiments (two or more factors) -- 2[superscript k] factorial experiments and fractions.
Physical Description:
xxiii, 816 pages : illustrations (some color) ;
Formatted Contents Note:
1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15.
Publication Date:
أ2007.
Title:
Probability & statistics for engineers & scientists / Ronald E. Walpole [and others]. Probability and statistics for engineers and scientists
Probability and statistics for engineers and scientists Probability and statistics for engineers and scientists
Author:
Walpole, Ronald E.
General Notes:
Includes bibliographical references (pages 655-657) and index.
2 Probability 22 -- 3 Random Variables and Probability Distributions 63 -- 4 Mathematical Expectation 88 -- 5 Some Discrete Probability Distributions 115 -- 6 Some Continuous Probability Distributions 142 -- 7 Functions of Random Variables (Optional) 177 -- 8 Fundamental Sampling Distributions and Data Descriptions 194 -- 9 One- and Two-Sample Estimation Problems 230 -- 10 One- and Two-Sample Tests of Hypotheses 284 -- 11 Simple Linear Regression and Correlation 350 -- 12 Multiple Linear Regression and Certain Nonlinear Regression Models 400 -- 13 One-Factor Experiments: General 461 -- 14 Factorial Experiments (Two or More Factors) 519 -- 15 2[superscript k] Factorial Experiments and Fractions 555 -- 16 Nonparametric Statistics 600 -- 17 Statistical Quality Control 625.
Publisher:
Prentice Hall,
Publication Place:
Upper Saddle River, NJ :
ISBN:
0130415294
9780130415295
0130984698
9780130984692
Subject:
Engineering. -- Statistical methods.
Probabilities.
Ing�enierie -- M�ethodes statistiques.
Probabilit�es.
Engineering -- Statistical methods.
Probabilities.
Statistik
Wahrscheinlichkeitsrechnung
ESTAT�ISTICA APLICADA.
PROBABILIDADE APLICADA.
ENGENHARIA.
Edition:
7th ed.
Contents:
Probability Random Variables and Probability Distributions Mathematical Expectation Some Discrete Probability Distributions Some Continuous Probability Distributions Functions of Random Variables (Optional) Fundamental Sampling Distributions and Data Descriptions One- and Two-Sample Estimation Problems One- and Two-Sample Tests of Hypotheses Simple Linear Regression and Correlation Multiple Linear Regression and Certain Nonlinear Regression Models One-Factor Experiments: General Factorial Experiments (Two or More Factors) 2[superscript k] Factorial Experiments and Fractions Nonparametric Statistics Statistical Quality Control
Physical Description:
xvi, 730 pages : illustrations (some color) ;
Formatted Contents Note:
2 22 -- 3 63 -- 4 88 -- 5 115 -- 6 142 -- 7 177 -- 8 194 -- 9 230 -- 10 284 -- 11 350 -- 12 400 -- 13 461 -- 14 519 -- 15 555 -- 16 600 -- 17 625.
Publication Date:
�2002.
Title:
Probability-1 Volume 1 / by Albert N. Shiryaev.
Graduate Texts in Mathematics,
Graduate texts in mathematics,
Author:
Shiryaev, Albert N. author.
SpringerLink (Online service)
General Notes:
Introduction -- Elementary Probability Theory -- Mathematical Foundations of Probability Theory -- Convergence of Probability Measures. Central Limit Theorem.
This book contains a systematic treatment of probability from the ground up, starting with intuitive ideas and gradually developing more sophisticated subjects, such as random walks, martingales, Markov chains, the measure-theoretic foundations of probability theory, weak convergence of probability measures, and the central limit theorem. Many examples are discussed in detail, and there are a large number of exercises. The book is accessible to advanced undergraduates and can be used as a text for independent study. To accommodate the greatly expanded material in the third edition of Probability, the book is now divided into two volumes. This first volume contains updated references and substantial revisions of the first three chapters of the second edition. In particular, new material has been added on generating functions, the inclusion-exclusion principle, theorems on monotonic classes (relying on a detailed treatment of “π-λ” systems), and the fundamental theorems of mathematical statistics.
Publisher:
Springer New York : Imprint: Springer,
Publication Place:
New York, NY :
ISBN:
9780387722061
Subject:
Mathematics.
Probabilities.
Mathematics.
Probability Theory and Stochastic Processes.
Series:
Graduate Texts in Mathematics, 95
Graduate texts in mathematics, 95
Edition:
3rd ed. 2016.
Contents:
Introduction -- Elementary Probability Theory -- Mathematical Foundations of Probability Theory -- Convergence of Probability Measures. Central Limit Theorem.
Physical Description:
XVII, 486 p. 39 illus. online resource.
Electronic Location:
http://dx.doi.org/10.1007/978-0-387-72206-1
Publication Date:
2016.
Title:
Probability: A Graduate Course A Graduate Course / by Allan Gut.
Springer Texts in Statistics,
Springer texts in statistics,
Author:
Gut, Allan. author.
SpringerLink (Online service)
General Notes:
Preface to the First Edition -- Preface to the Second Edition -- Outline of Contents -- Notation and Symbols -- Introductory Measure Theory -- Random Variables -- Inequalities -- Characteristic Functions -- Convergence -- The Law of Large Numbers -- The Central Limit Theorem -- The Law of the Iterated Logarithm -- Limited Theorems -- Martingales -- Some Useful Mathematics -- References -- Index.
Like its predecessor, this book starts from the premise that, rather than being a purely mathematical discipline, probability theory is an intimate companion of statistics. The book starts with the basic tools, and goes on to cover a number of subjects in detail, including chapters on inequalities, characteristic functions and convergence. This is followed by a thorough treatment of the three main subjects in probability theory: the law of large numbers, the central limit theorem, and the law of the iterated logarithm. After a discussion of generalizations and extensions, the book concludes with an extensive chapter on martingales. The new edition is comprehensively updated, including some new material as well as around a dozen new references.
Publisher:
Springer New York : Imprint: Springer,
Publication Place:
New York, NY :
ISBN:
9781461447085
Subject:
Mathematics.
Distribution (Probability theory).
Statistics.
Mathematical statistics.
Mathematics.
Probability Theory and Stochastic Processes.
Statistical Theory and Methods.
Statistics, general.
Series:
Springer Texts in Statistics, 75
Springer texts in statistics, 75
Edition:
2nd ed. 2013.
Contents:
Preface to the First Edition -- Preface to the Second Edition -- Outline of Contents -- Notation and Symbols -- Introductory Measure Theory -- Random Variables -- Inequalities -- Characteristic Functions -- Convergence -- The Law of Large Numbers -- The Central Limit Theorem -- The Law of the Iterated Logarithm -- Limited Theorems -- Martingales -- Some Useful Mathematics -- References -- Index.
Physical Description:
XXV, 600 p. 13 illus. online resource.
Electronic Location:
http://dx.doi.org/10.1007/978-1-4614-4708-5
Publication Date:
2013.
Title:
Self-Normalized Processes Limit Theory and Statistical Applications / by Victor H. Peña, Tze Leung Lai, Qi-Man Shao.
Probability and its Applications,
Probability and its applications,
Author:
Peña, Victor H.
Lai, Tze Leung.
Shao, Qi-Man.
SpringerLink (Online service)
General Notes:
<P>1. Introduction -- Part I Independent Random Variables -- 2. Classical Limit Theorems and Preliminary Tools -- 3. Self-Normalized Large Deviations -- 4. Weak Convergence of Self-Normalized Sums -- 5. Stein’s Method and Self-Normalized Berry–Esseen Inequality -- 6. Self-Normalized Moderate Deviations and Law of the Iterated Logarithm -- 7. Cramér-type Moderate Deviations for Self-Normalized Sums -- 8. Self-Normalized Empirical Processes and U-Statistics -- Part II Martingales and Dependent Random Vectors -- 9. Martingale Inequalities and Related Tools -- 10. A General Framework for Self-Normalization -- 11. Pseudo-Maximization via Method of Mixtures -- 12. Moment and Exponential Inequalities for Self-Normalized Processes -- 13. Laws of the Iterated Logarithm for Self-Normalized Processes and Martingales -- 14. Multivariate Matrix-Normalized Processes -- Part III Statistical Applications -- 15. The t-Statistic and Studentized Statistics -- 16. Self-Normalization and Approximate Pivots for Bootstrapping -- 17. Self-Normalized Martingales and Pseudo-Maximization in Likelihood or Bayesian Inference -- 18. Information Bounds and Boundary Crossing Probabilities for Self-Normalized Statistics in Sequential Analysis -- References -- Index. </P>.
<P>Self-normalized processes are of common occurrence in probabilistic and statistical studies. A prototypical example is Student's t-statistic introduced in 1908 by Gosset, whose portrait is on the front cover. Due to the highly non-linear nature of these processes, the theory experienced a long period of slow development. In recent years there have been a number of important advances in the theory and applications of self-normalized processes. Some of these developments are closely linked to the study of central limit theorems, which imply that self-normalized processes are approximate pivots for statistical inference.</P> <P>The present volume covers recent developments in the area, including self-normalized large and moderate deviations, and laws of the iterated logarithms for self-normalized martingales. This is the first book that systematically treats the theory and applications of self-normalization.</P>
Publisher:
Springer Berlin Heidelberg,
Publication Place:
Berlin, Heidelberg :
ISBN:
9783540856368
Subject:
Mathematics.
Distribution (Probability theory).
Mathematical statistics.
Mathematics.
Probability Theory and Stochastic Processes.
Statistical Theory and Methods.
Series:
Probability and its Applications,
Probability and its applications,
Contents:
<P>1. Introduction -- Part I Independent Random Variables -- 2. Classical Limit Theorems and Preliminary Tools -- 3. Self-Normalized Large Deviations -- 4. Weak Convergence of Self-Normalized Sums -- 5. Stein’s Method and Self-Normalized Berry–Esseen Inequality -- 6. Self-Normalized Moderate Deviations and Law of the Iterated Logarithm -- 7. Cramér-type Moderate Deviations for Self-Normalized Sums -- 8. Self-Normalized Empirical Processes and U-Statistics -- Part II Martingales and Dependent Random Vectors -- 9. Martingale Inequalities and Related Tools -- 10. A General Framework for Self-Normalization -- 11. Pseudo-Maximization via Method of Mixtures -- 12. Moment and Exponential Inequalities for Self-Normalized Processes -- 13. Laws of the Iterated Logarithm for Self-Normalized Processes and Martingales -- 14. Multivariate Matrix-Normalized Processes -- Part III Statistical Applications -- 15. The t-Statistic and Studentized Statistics -- 16. Self-Normalization and Approximate Pivots for Bootstrapping -- 17. Self-Normalized Martingales and Pseudo-Maximization in Likelihood or Bayesian Inference -- 18. Information Bounds and Boundary Crossing Probabilities for Self-Normalized Statistics in Sequential Analysis -- References -- Index. </P>.
Physical Description:
digital.
Electronic Location:
http://dx.doi.org/10.1007/978-3-540-85636-8
Publication Date:
2009.
Title:
Self-Normalized Processes Limit Theory and Statistical Applications / by Victor H. Peña, Tze Leung Lai, Qi-Man Shao.
Probability and its Applications,
Probability and its applications,
Author:
Peña, Victor H.
Lai, Tze Leung.
Shao, Qi-Man.
SpringerLink (Online service)
General Notes:
<P>1. Introduction -- Part I Independent Random Variables -- 2. Classical Limit Theorems and Preliminary Tools -- 3. Self-Normalized Large Deviations -- 4. Weak Convergence of Self-Normalized Sums -- 5. Stein’s Method and Self-Normalized Berry–Esseen Inequality -- 6. Self-Normalized Moderate Deviations and Law of the Iterated Logarithm -- 7. Cramér-type Moderate Deviations for Self-Normalized Sums -- 8. Self-Normalized Empirical Processes and U-Statistics -- Part II Martingales and Dependent Random Vectors -- 9. Martingale Inequalities and Related Tools -- 10. A General Framework for Self-Normalization -- 11. Pseudo-Maximization via Method of Mixtures -- 12. Moment and Exponential Inequalities for Self-Normalized Processes -- 13. Laws of the Iterated Logarithm for Self-Normalized Processes and Martingales -- 14. Multivariate Matrix-Normalized Processes -- Part III Statistical Applications -- 15. The t-Statistic and Studentized Statistics -- 16. Self-Normalization and Approximate Pivots for Bootstrapping -- 17. Self-Normalized Martingales and Pseudo-Maximization in Likelihood or Bayesian Inference -- 18. Information Bounds and Boundary Crossing Probabilities for Self-Normalized Statistics in Sequential Analysis -- References -- Index. </P>.
<P>Self-normalized processes are of common occurrence in probabilistic and statistical studies. A prototypical example is Student's t-statistic introduced in 1908 by Gosset, whose portrait is on the front cover. Due to the highly non-linear nature of these processes, the theory experienced a long period of slow development. In recent years there have been a number of important advances in the theory and applications of self-normalized processes. Some of these developments are closely linked to the study of central limit theorems, which imply that self-normalized processes are approximate pivots for statistical inference.</P> <P>The present volume covers recent developments in the area, including self-normalized large and moderate deviations, and laws of the iterated logarithms for self-normalized martingales. This is the first book that systematically treats the theory and applications of self-normalization.</P>
Publisher:
Springer Berlin Heidelberg,
Publication Place:
Berlin, Heidelberg :
ISBN:
9783540856368
Subject:
Mathematics.
Distribution (Probability theory).
Mathematical statistics.
Mathematics.
Probability Theory and Stochastic Processes.
Statistical Theory and Methods.
Series:
Probability and its Applications,
Probability and its applications,
Contents:
<P>1. Introduction -- Part I Independent Random Variables -- 2. Classical Limit Theorems and Preliminary Tools -- 3. Self-Normalized Large Deviations -- 4. Weak Convergence of Self-Normalized Sums -- 5. Stein’s Method and Self-Normalized Berry–Esseen Inequality -- 6. Self-Normalized Moderate Deviations and Law of the Iterated Logarithm -- 7. Cramér-type Moderate Deviations for Self-Normalized Sums -- 8. Self-Normalized Empirical Processes and U-Statistics -- Part II Martingales and Dependent Random Vectors -- 9. Martingale Inequalities and Related Tools -- 10. A General Framework for Self-Normalization -- 11. Pseudo-Maximization via Method of Mixtures -- 12. Moment and Exponential Inequalities for Self-Normalized Processes -- 13. Laws of the Iterated Logarithm for Self-Normalized Processes and Martingales -- 14. Multivariate Matrix-Normalized Processes -- Part III Statistical Applications -- 15. The t-Statistic and Studentized Statistics -- 16. Self-Normalization and Approximate Pivots for Bootstrapping -- 17. Self-Normalized Martingales and Pseudo-Maximization in Likelihood or Bayesian Inference -- 18. Information Bounds and Boundary Crossing Probabilities for Self-Normalized Statistics in Sequential Analysis -- References -- Index. </P>.
Physical Description:
digital.
Electronic Location:
http://dx.doi.org/10.1007/978-3-540-85636-8
Publication Date:
2009.
Title:
The Doctrine of Chances Probabilistic Aspects of Gambling / by Stewart N. Ethier.
Probability and its Applications,
Probability and its applications,
Author:
Ethier, Stewart N.
SpringerLink (Online service)
General Notes:
<P>Preface -- Part I Theory. 1. Review of Probability. 2. Conditional Expectation. 3. Martingales. 4. Markov Chains. 5. Game Theory. 6. House Advantage. 7. Gambler’s Ruin. 8. Betting Systems. 9. Bold Play. 10. Optimal Proportional Play. 11. Card Theory -- Part II Applications. 12. Slot Machines. 13. Roulette. 14. Keno. 15. Craps. 17. Video Poke. 18. Faro. 19. Baccarat. 20. Trente et Quarante. 21. Twenty-One. 22. Poker -- A Appendix. A.1. Results from algebra and number theory. A.2.Results from analysis and probability -- List of Notations. Answers to Selected Problems. References -- Index.</P>.
<P>Three centuries ago Montmort and De Moivre published two of the first books on probability theory, then called the doctrine of chances, emphasizing its most important application at that time, games of chance. This volume, on the probabilistic aspects of gambling, is a modern version of those classics. While covering the classical material such as house advantage and gambler's ruin, it also takes up such 20<SUP>th</SUP>-century topics as martingales, Markov chains, game theory, bold play, and optimal proportional play. In addition there is extensive coverage of specific casino games such as roulette, craps, video poker, baccarat, and twenty-one.</P> The volume addresses researchers and graduate students in probability theory, stochastic processes, game theory, operations research, statistics but it is also accessible to undergraduate students, who have had a course in probability.
Publisher:
Springer Berlin Heidelberg,
Publication Place:
Berlin, Heidelberg :
ISBN:
9783540787839
Subject:
Mathematics.
Distribution (Probability theory).
Mathematics.
Probability Theory and Stochastic Processes.
Game Theory, Economics, Social and Behav. Sciences.
Series:
Probability and its Applications,
Probability and its applications,
Contents:
<P>Preface -- Part I Theory. 1. Review of Probability. 2. Conditional Expectation. 3. Martingales. 4. Markov Chains. 5. Game Theory. 6. House Advantage. 7. Gambler’s Ruin. 8. Betting Systems. 9. Bold Play. 10. Optimal Proportional Play. 11. Card Theory -- Part II Applications. 12. Slot Machines. 13. Roulette. 14. Keno. 15. Craps. 17. Video Poke. 18. Faro. 19. Baccarat. 20. Trente et Quarante. 21. Twenty-One. 22. Poker -- A Appendix. A.1. Results from algebra and number theory. A.2.Results from analysis and probability -- List of Notations. Answers to Selected Problems. References -- Index.</P>.
Physical Description:
XIV, 816p. digital.
Electronic Location:
http://dx.doi.org/10.1007/978-3-540-78783-9
Publication Date:
2010.
Title:
The Doctrine of Chances Probabilistic Aspects of Gambling / by Stewart N. Ethier.
Probability and its Applications,
Probability and its applications,
Author:
Ethier, Stewart N.
SpringerLink (Online service)
General Notes:
<P>Preface -- Part I Theory. 1. Review of Probability. 2. Conditional Expectation. 3. Martingales. 4. Markov Chains. 5. Game Theory. 6. House Advantage. 7. Gambler’s Ruin. 8. Betting Systems. 9. Bold Play. 10. Optimal Proportional Play. 11. Card Theory -- Part II Applications. 12. Slot Machines. 13. Roulette. 14. Keno. 15. Craps. 17. Video Poke. 18. Faro. 19. Baccarat. 20. Trente et Quarante. 21. Twenty-One. 22. Poker -- A Appendix. A.1. Results from algebra and number theory. A.2.Results from analysis and probability -- List of Notations. Answers to Selected Problems. References -- Index.</P>.
<P>Three centuries ago Montmort and De Moivre published two of the first books on probability theory, then called the doctrine of chances, emphasizing its most important application at that time, games of chance. This volume, on the probabilistic aspects of gambling, is a modern version of those classics. While covering the classical material such as house advantage and gambler's ruin, it also takes up such 20<SUP>th</SUP>-century topics as martingales, Markov chains, game theory, bold play, and optimal proportional play. In addition there is extensive coverage of specific casino games such as roulette, craps, video poker, baccarat, and twenty-one.</P> The volume addresses researchers and graduate students in probability theory, stochastic processes, game theory, operations research, statistics but it is also accessible to undergraduate students, who have had a course in probability.
Publisher:
Springer Berlin Heidelberg,
Publication Place:
Berlin, Heidelberg :
ISBN:
9783540787839
Subject:
Mathematics.
Distribution (Probability theory).
Mathematics.
Probability Theory and Stochastic Processes.
Game Theory, Economics, Social and Behav. Sciences.
Series:
Probability and its Applications,
Probability and its applications,
Contents:
<P>Preface -- Part I Theory. 1. Review of Probability. 2. Conditional Expectation. 3. Martingales. 4. Markov Chains. 5. Game Theory. 6. House Advantage. 7. Gambler’s Ruin. 8. Betting Systems. 9. Bold Play. 10. Optimal Proportional Play. 11. Card Theory -- Part II Applications. 12. Slot Machines. 13. Roulette. 14. Keno. 15. Craps. 17. Video Poke. 18. Faro. 19. Baccarat. 20. Trente et Quarante. 21. Twenty-One. 22. Poker -- A Appendix. A.1. Results from algebra and number theory. A.2.Results from analysis and probability -- List of Notations. Answers to Selected Problems. References -- Index.</P>.
Physical Description:
XIV, 816p. digital.
Electronic Location:
http://dx.doi.org/10.1007/978-3-540-78783-9
Publication Date:
2010.
Title:
Basics of Applied Stochastic Processes by Richard Serfozo.
Probability and Its Applications,
Probability and its applications,
Author:
Serfozo, Richard.
SpringerLink (Online service)
General Notes:
<P>1. Markov Chains -- 2. Renewal and Regenerative Processes -- 3. Poisson Processes -- 4. Continuous-Time Markov Chains -- 5. Brownian Motion -- 6. Appendix -- References -- Notation -- Index.</P>.
<P>Stochastic processes are mathematical models of random phenomena that evolve according to prescribed dynamics. Processes commonly used in applications are Markov chains in discrete and continuous time, renewal and regenerative processes, Poisson processes, and Brownian motion. This volume gives an in-depth description of the structure and basic properties of these stochastic processes. A main focus is on equilibrium distributions, strong laws of large numbers, and ordinary and functional central limit theorems for cost and performance parameters. Although these results differ for various processes, they have a common trait of being limit theorems for processes with regenerative increments. Extensive examples and exercises show how to formulate stochastic models of systems as functions of a system’s data and dynamics, and how to represent and analyze cost and performance measures. Topics include stochastic networks, spatial and space-time Poisson processes, queueing, reversible processes, simulation, Brownian approximations, and varied Markovian models. </P> <P></P> <P>The technical level of the volume is between that of introductory texts that focus on highlights of applied stochastic processes, and advanced texts that focus on theoretical aspects of processes. Intended readers are researchers and graduate students in mathematics, statistics, operations research, computer science, engineering, and business.</P>
Publisher:
Springer Berlin Heidelberg : Imprint: Springer,
Publication Place:
Berlin, Heidelberg :
ISBN:
9783540893325
Subject:
Mathematics.
Distribution (Probability theory).
Mathematics.
Probability Theory and Stochastic Processes.
Series:
Probability and Its Applications,
Probability and its applications,
Contents:
<P>1. Markov Chains -- 2. Renewal and Regenerative Processes -- 3. Poisson Processes -- 4. Continuous-Time Markov Chains -- 5. Brownian Motion -- 6. Appendix -- References -- Notation -- Index.</P>.
Physical Description:
digital.
Electronic Location:
http://dx.doi.org/10.1007/978-3-540-89332-5
Publication Date:
2009.
Title:
Basics of Applied Stochastic Processes by Richard Serfozo.
Probability and Its Applications,
Probability and its applications,
Author:
Serfozo, Richard.
SpringerLink (Online service)
General Notes:
<P>1. Markov Chains -- 2. Renewal and Regenerative Processes -- 3. Poisson Processes -- 4. Continuous-Time Markov Chains -- 5. Brownian Motion -- 6. Appendix -- References -- Notation -- Index.</P>.
<P>Stochastic processes are mathematical models of random phenomena that evolve according to prescribed dynamics. Processes commonly used in applications are Markov chains in discrete and continuous time, renewal and regenerative processes, Poisson processes, and Brownian motion. This volume gives an in-depth description of the structure and basic properties of these stochastic processes. A main focus is on equilibrium distributions, strong laws of large numbers, and ordinary and functional central limit theorems for cost and performance parameters. Although these results differ for various processes, they have a common trait of being limit theorems for processes with regenerative increments. Extensive examples and exercises show how to formulate stochastic models of systems as functions of a system’s data and dynamics, and how to represent and analyze cost and performance measures. Topics include stochastic networks, spatial and space-time Poisson processes, queueing, reversible processes, simulation, Brownian approximations, and varied Markovian models. </P> <P></P> <P>The technical level of the volume is between that of introductory texts that focus on highlights of applied stochastic processes, and advanced texts that focus on theoretical aspects of processes. Intended readers are researchers and graduate students in mathematics, statistics, operations research, computer science, engineering, and business.</P>
Publisher:
Springer Berlin Heidelberg : Imprint: Springer,
Publication Place:
Berlin, Heidelberg :
ISBN:
9783540893325
Subject:
Mathematics.
Distribution (Probability theory).
Mathematics.
Probability Theory and Stochastic Processes.
Series:
Probability and Its Applications,
Probability and its applications,
Contents:
<P>1. Markov Chains -- 2. Renewal and Regenerative Processes -- 3. Poisson Processes -- 4. Continuous-Time Markov Chains -- 5. Brownian Motion -- 6. Appendix -- References -- Notation -- Index.</P>.
Physical Description:
digital.
Electronic Location:
http://dx.doi.org/10.1007/978-3-540-89332-5
Publication Date:
2009.
Title:
Probability Measures on Semigroups Convolution Products, Random Walks and Random Matrices / by Göran Högnäs, Arunava Mukherjea.
Probability and Its Applications,
Probability and its applications,
Author:
Högnäs, Göran.
Mukherjea, Arunava.
SpringerLink (Online service)
General Notes:
Semigroups -- Probability Measures on Topological Semigroups -- Random Walks on Semigroups -- Random Matrices -- Index.
Semigroups are very general structures and scientists often come across them in various contexts in science and engineering. In this second edition of Probability Measures on Semigroups, first published in the University Series in Mathematics in 1996, the authors present the theory of weak convergence of convolution products of probability measures on semigroups, the theory of random walks on semigroups, and their applications to products of random matrices. They examine the essentials of abstract semigroup theory and its application to concrete semigroups of matrices. They present results on weak convergence, random walks, random matrices using semigroup ideas that for the most part are complete and best possible. Still, as the authors point out, there are other results that remain to be completed. These are all mentioned in the notes and comments at the end of each chapter, and will keep the readership of this book enthusiastic and interested for some time to come. Apart from corrections of several errors, new results have been added in the main text and in the appendices; the references, all notes and comments at the end of each chapter have been updated, and exercises have been added. This volume is suitable for a one semester course on semigroups and it could be used as a main text or supplementary material for courses focusing on probability on algebraic structures or weak convergence. It is ideally suited to graduate students in mathematics, and in other fields such as engineering and sciences with an interest in probability. Students in statistics using advance probability will also find it useful. 'A well-written book...This is elegant mathematics, motivated by examples and presented in an accessible way that engages the reader.' International Statistics Institute, December 1996 'This beautiful book...guides the reader through the most important developments...a valuable addition to the library of the probabilist, and a must for anybody interested in probability on algebraic structures.' Zentralblatt für Mathematik und ihre Grenzgebiete-Mathematical Abstracts 'This well-written volume, by two of the most successful workers in the field....deserves to become the standard introduction for beginning researchers in this field.' Journal of the Royal Statistical Society
Publisher:
Springer US,
Publication Place:
Boston, MA :
ISBN:
9780387775487
Subject:
Mathematics.
Computer science.
Topological groups.
Global analysis (Mathematics).
Distribution (Probability theory).
Mathematics.
Probability Theory and Stochastic Processes.
Probability and Statistics in Computer Science.
Topological Groups, Lie Groups.
ANALYSIS.
Series:
Probability and Its Applications,
Probability and its applications,
Edition:
2.
Contents:
Semigroups -- Probability Measures on Topological Semigroups -- Random Walks on Semigroups -- Random Matrices -- Index.
Physical Description:
XII, 432 p. digital.
Electronic Location:
http://dx.doi.org/10.1007/978-0-387-77548-7
Publication Date:
2011.
Title:
Probability Measures on Semigroups Convolution Products, Random Walks and Random Matrices / by Göran Högnäs, Arunava Mukherjea.
Probability and Its Applications,
Probability and its applications,
Author:
Högnäs, Göran.
Mukherjea, Arunava.
SpringerLink (Online service)
General Notes:
Semigroups -- Probability Measures on Topological Semigroups -- Random Walks on Semigroups -- Random Matrices -- Index.
Semigroups are very general structures and scientists often come across them in various contexts in science and engineering. In this second edition of Probability Measures on Semigroups, first published in the University Series in Mathematics in 1996, the authors present the theory of weak convergence of convolution products of probability measures on semigroups, the theory of random walks on semigroups, and their applications to products of random matrices. They examine the essentials of abstract semigroup theory and its application to concrete semigroups of matrices. They present results on weak convergence, random walks, random matrices using semigroup ideas that for the most part are complete and best possible. Still, as the authors point out, there are other results that remain to be completed. These are all mentioned in the notes and comments at the end of each chapter, and will keep the readership of this book enthusiastic and interested for some time to come. Apart from corrections of several errors, new results have been added in the main text and in the appendices; the references, all notes and comments at the end of each chapter have been updated, and exercises have been added. This volume is suitable for a one semester course on semigroups and it could be used as a main text or supplementary material for courses focusing on probability on algebraic structures or weak convergence. It is ideally suited to graduate students in mathematics, and in other fields such as engineering and sciences with an interest in probability. Students in statistics using advance probability will also find it useful. 'A well-written book...This is elegant mathematics, motivated by examples and presented in an accessible way that engages the reader.' International Statistics Institute, December 1996 'This beautiful book...guides the reader through the most important developments...a valuable addition to the library of the probabilist, and a must for anybody interested in probability on algebraic structures.' Zentralblatt für Mathematik und ihre Grenzgebiete-Mathematical Abstracts 'This well-written volume, by two of the most successful workers in the field....deserves to become the standard introduction for beginning researchers in this field.' Journal of the Royal Statistical Society
Publisher:
Springer US,
Publication Place:
Boston, MA :
ISBN:
9780387775487
Subject:
Mathematics.
Computer science.
Topological groups.
Global analysis (Mathematics).
Distribution (Probability theory).
Mathematics.
Probability Theory and Stochastic Processes.
Probability and Statistics in Computer Science.
Topological Groups, Lie Groups.
ANALYSIS.
Series:
Probability and Its Applications,
Probability and its applications,
Edition:
2.
Contents:
Semigroups -- Probability Measures on Topological Semigroups -- Random Walks on Semigroups -- Random Matrices -- Index.
Physical Description:
XII, 432 p. digital.
Electronic Location:
http://dx.doi.org/10.1007/978-0-387-77548-7
Publication Date:
2011.
Title:
The Poisson-Dirichlet Distribution and Related Topics Models and Asymptotic Behaviors / by Shui Feng.
Probability and its Applications,
Probability and its applications,
Author:
Feng, Shui.
SpringerLink (Online service)
General Notes:
Preface -- Part I: Models -- 1. Introduction -- 2. The Poisson–Dirichlet Distribution -- 3. The Two-Parameter Poisson–Dirichlet Distribution -- 4. The Coalescent -- 5. Stochastic Dynamics -- 6. Particle Representation -- Part II: Asymptotic Behaviors -- 7. Fluctuation Theorems -- 8. Large Deviations for the Poisson–Dirichlet Distribution -- 9. Large Deviations for the Dirichlet Processes -- A. Poisson Process and Poisson Random Measure -- A.1. Definitions -- A.2. Properties -- B. Basics of Large Deviations -- References -- Index.
The Poisson-Dirichlet distribution is an infinite dimensional probability distribution. It was introduced by Kingman over thirty years ago, and has found applications in a broad range of areas including Bayesian statistics, combinatorics, differential geometry, economics, number theory, physics, and population genetics. This monograph provides a comprehensive study of this distribution and some related topics, with particular emphasis on recent progresses in evolutionary dynamics and asymptotic behaviors. One central scheme is the unification of the Poisson-Dirichlet distribution, the urn structure, the coalescent, the evolutionary dynamics through the grand particle system of Donnelly and Kurtz. It is largely self-contained. The methods and techniques used in it appeal to researchers in a wide variety of subjects.
Publisher:
Springer Berlin Heidelberg,
Publication Place:
Berlin, Heidelberg :
ISBN:
9783642111945
Subject:
Mathematics.
Biology -- Mathematics.
Distribution (Probability theory).
Mathematics.
Probability Theory and Stochastic Processes.
Mathematical Biology in General.
Series:
Probability and its Applications,
Probability and its applications,
Contents:
Preface -- Part I: Models -- 1. Introduction -- 2. The Poisson–Dirichlet Distribution -- 3. The Two-Parameter Poisson–Dirichlet Distribution -- 4. The Coalescent -- 5. Stochastic Dynamics -- 6. Particle Representation -- Part II: Asymptotic Behaviors -- 7. Fluctuation Theorems -- 8. Large Deviations for the Poisson–Dirichlet Distribution -- 9. Large Deviations for the Dirichlet Processes -- A. Poisson Process and Poisson Random Measure -- A.1. Definitions -- A.2. Properties -- B. Basics of Large Deviations -- References -- Index.
Physical Description:
XII, 218p. digital.
Electronic Location:
http://dx.doi.org/10.1007/978-3-642-11194-5
Publication Date:
2010.
Title:
The Poisson-Dirichlet Distribution and Related Topics Models and Asymptotic Behaviors / by Shui Feng.
Probability and its Applications,
Probability and its applications,
Author:
Feng, Shui.
SpringerLink (Online service)
General Notes:
Preface -- Part I: Models -- 1. Introduction -- 2. The Poisson–Dirichlet Distribution -- 3. The Two-Parameter Poisson–Dirichlet Distribution -- 4. The Coalescent -- 5. Stochastic Dynamics -- 6. Particle Representation -- Part II: Asymptotic Behaviors -- 7. Fluctuation Theorems -- 8. Large Deviations for the Poisson–Dirichlet Distribution -- 9. Large Deviations for the Dirichlet Processes -- A. Poisson Process and Poisson Random Measure -- A.1. Definitions -- A.2. Properties -- B. Basics of Large Deviations -- References -- Index.
The Poisson-Dirichlet distribution is an infinite dimensional probability distribution. It was introduced by Kingman over thirty years ago, and has found applications in a broad range of areas including Bayesian statistics, combinatorics, differential geometry, economics, number theory, physics, and population genetics. This monograph provides a comprehensive study of this distribution and some related topics, with particular emphasis on recent progresses in evolutionary dynamics and asymptotic behaviors. One central scheme is the unification of the Poisson-Dirichlet distribution, the urn structure, the coalescent, the evolutionary dynamics through the grand particle system of Donnelly and Kurtz. It is largely self-contained. The methods and techniques used in it appeal to researchers in a wide variety of subjects.
Publisher:
Springer Berlin Heidelberg,
Publication Place:
Berlin, Heidelberg :
ISBN:
9783642111945
Subject:
Mathematics.
Biology -- Mathematics.
Distribution (Probability theory).
Mathematics.
Probability Theory and Stochastic Processes.
Mathematical Biology in General.
Series:
Probability and its Applications,
Probability and its applications,
Contents:
Preface -- Part I: Models -- 1. Introduction -- 2. The Poisson–Dirichlet Distribution -- 3. The Two-Parameter Poisson–Dirichlet Distribution -- 4. The Coalescent -- 5. Stochastic Dynamics -- 6. Particle Representation -- Part II: Asymptotic Behaviors -- 7. Fluctuation Theorems -- 8. Large Deviations for the Poisson–Dirichlet Distribution -- 9. Large Deviations for the Dirichlet Processes -- A. Poisson Process and Poisson Random Measure -- A.1. Definitions -- A.2. Properties -- B. Basics of Large Deviations -- References -- Index.
Physical Description:
XII, 218p. digital.
Electronic Location:
http://dx.doi.org/10.1007/978-3-642-11194-5
Publication Date:
2010.
Title:
Stochastic Differential Equations in Infinite Dimensions with Applications to Stochastic Partial Differential Equations / by Leszek Gawarecki, Vidyadhar Mandrekar.
Probability and Its Applications,
Probability and its applications,
Author:
Gawarecki, Leszek.
Mandrekar, Vidyadhar.
SpringerLink (Online service)
General Notes:
Preface -- Part I: Stochastic Differential Equations in Infinite Dimensions -- 1.Partial Differential Equations as Equations in Infinite -- 2.Stochastic Calculus -- 3.Stochastic Differential Equations -- 4.Solutions by Variational Method -- 5.Stochastic Differential Equations with Discontinuous Drift -- Part II: Stability, Boundedness, and Invariant Measures -- 6.Stability Theory for Strong and Mild Solutions -- 7.Ultimate Boundedness and Invariant Measure -- References -- Index.
The systematic study of existence, uniqueness, and properties of solutions to stochastic differential equations in infinite dimensions arising from practical problems characterizes this volume that is intended for graduate students and for pure and applied mathematicians, physicists, engineers, professionals working with mathematical models of finance. Major methods include compactness, coercivity, monotonicity, in a variety of set-ups. The authors emphasize the fundamental work of Gikhman and Skorokhod on the existence and uniqueness of solutions to stochastic differential equations and present its extension to infinite dimension. They also generalize the work of Khasminskii on stability and stationary distributions of solutions. New results, applications, and examples of stochastic partial differential equations are included. This clear and detailed presentation gives the basics of the infinite dimensional version of the classic books of Gikhman and Skorokhod and of Khasminskii in one concise volume that covers the main topics in infinite dimensional stochastic PDE’s. By appropriate selection of material, the volume can be adapted for a 1- or 2-semester course, and can prepare the reader for research in this rapidly expanding area.
Publisher:
Springer Berlin Heidelberg,
Publication Place:
Berlin, Heidelberg :
ISBN:
9783642161940
Subject:
Mathematics.
Differential equations, Partial.
Finance.
Distribution (Probability theory).
Mathematics.
Probability Theory and Stochastic Processes.
Partial differential equations.
Quantitative Finance.
Applications of Mathematics.
Series:
Probability and Its Applications,
Probability and its applications,
Contents:
Preface -- Part I: Stochastic Differential Equations in Infinite Dimensions -- 1.Partial Differential Equations as Equations in Infinite -- 2.Stochastic Calculus -- 3.Stochastic Differential Equations -- 4.Solutions by Variational Method -- 5.Stochastic Differential Equations with Discontinuous Drift -- Part II: Stability, Boundedness, and Invariant Measures -- 6.Stability Theory for Strong and Mild Solutions -- 7.Ultimate Boundedness and Invariant Measure -- References -- Index.
Physical Description:
XVI, 292 p. digital.
Electronic Location:
http://dx.doi.org/10.1007/978-3-642-16194-0
Publication Date:
2011.
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