Miguel González Velasco, Inés María Del Puerto García, George Petrov Yanev
Controlled Branching Processes (eBook, PDF)
139,99 €
139,99 €
inkl. MwSt.
Sofort per Download lieferbar
0 °P sammeln
139,99 €
Als Download kaufen
139,99 €
inkl. MwSt.
Sofort per Download lieferbar
0 °P sammeln
Jetzt verschenken
Alle Infos zum eBook verschenken
139,99 €
inkl. MwSt.
Sofort per Download lieferbar
Alle Infos zum eBook verschenken
0 °P sammeln
Miguel González Velasco, Inés María Del Puerto García, George Petrov Yanev
Controlled Branching Processes (eBook, PDF)
- Format: PDF
- Merkliste
- Auf die Merkliste
- Bewerten Bewerten
- Teilen
- Produkt teilen
- Produkterinnerung
- Produkterinnerung

Bitte loggen Sie sich zunächst in Ihr Kundenkonto ein oder registrieren Sie sich bei
bücher.de, um das eBook-Abo tolino select nutzen zu können.
Hier können Sie sich einloggen
Hier können Sie sich einloggen
Sie sind bereits eingeloggt. Klicken Sie auf 2. tolino select Abo, um fortzufahren.

Bitte loggen Sie sich zunächst in Ihr Kundenkonto ein oder registrieren Sie sich bei bücher.de, um das eBook-Abo tolino select nutzen zu können.
The purpose of this book is to provide a comprehensive discussion of the available results for discrete time branching processes with random control functions. The independence of individuals' reproduction is a fundamental assumption in the classical branching processes. Alternatively, the controlled branching processes (CBPs) allow the number of reproductive individuals in one generation to decrease or increase depending on the size of the previous generation. Generating a wide range of behaviors, the CBPs have been successfully used as modeling tools in diverse areas of applications.
- Geräte: PC
- mit Kopierschutz
- eBook Hilfe
- Größe: 3.74MB
Andere Kunden interessierten sich auch für
- Götz KerstingDiscrete Time Branching Processes in Random Environment (eBook, PDF)139,99 €
- Branching Processes (eBook, PDF)73,95 €
- Marie ReillyControlled Epidemiological Studies (eBook, PDF)52,95 €
- Classical and Modern Branching Processes (eBook, PDF)73,95 €
- Paddy FarringtonSelf-Controlled Case Series Studies (eBook, PDF)40,95 €
- I. I. GihmanControlled Stochastic Processes (eBook, PDF)40,95 €
- Anne WhiteheadMeta-Analysis of Controlled Clinical Trials (eBook, PDF)123,99 €
-
-
-
The purpose of this book is to provide a comprehensive discussion of the available results for discrete time branching processes with random control functions. The independence of individuals' reproduction is a fundamental assumption in the classical branching processes. Alternatively, the controlled branching processes (CBPs) allow the number of reproductive individuals in one generation to decrease or increase depending on the size of the previous generation. Generating a wide range of behaviors, the CBPs have been successfully used as modeling tools in diverse areas of applications.
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in D ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: John Wiley & Sons
- Erscheinungstermin: 27. Dezember 2017
- Englisch
- ISBN-13: 9781119484646
- Artikelnr.: 50877618
- Verlag: John Wiley & Sons
- Erscheinungstermin: 27. Dezember 2017
- Englisch
- ISBN-13: 9781119484646
- Artikelnr.: 50877618
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
Miguel González Velasco is Associate Professor at the University of Extremadura in Spain. His research interests lie in the theory of branching processes and its application to genetics, epidemiology and population dynamics.
Inés M. del Puerto García is Associate Professor at the University of Extremadura in Spain. Her research interests include the study of the probabilistic and inferential theory on branching processes.
George P. Yanev is Associate Professor at the University of Texas Rio Grande Valley in the USA. His research interests include branching processes and characterizations of probability distributions.
Inés M. del Puerto García is Associate Professor at the University of Extremadura in Spain. Her research interests include the study of the probabilistic and inferential theory on branching processes.
George P. Yanev is Associate Professor at the University of Texas Rio Grande Valley in the USA. His research interests include branching processes and characterizations of probability distributions.
Foreword ix
Preface xi
Chapter 1 Classical Branching Models 1
1.1 Bienaymé-Galton-Watson process 1
1.1.1 Moments and probability of extinction 4
1.1.2 Limit theorems 9
1.2 Processes with unrestricted immigration 17
1.2.1 Limit theorems 21
1.2.2 Critical process with decreasing to zero immigration 25
1.3 Processes with immigration after empty generation only 29
1.3.1 Limit theorems 31
1.3.2 Critical process with decreasing to zero immigration 36
1.4 Background and bibliographical notes 40
Chapter 2 Branching Processes with Migration 43
2.1 Galton-Watson process with migration 43
2.2 Limit theorems 47
2.2.1 Non-critical processes 47
2.2.2 Critical processes with non-negative migration mean 49
2.2.3 Critical processes with negative migration mean 52
2.3 Regeneration and migration 55
2.3.1 Alternating regenerative processes 56
2.3.2 An extension of Galton-Watson processes with migration 58
2.4 Background and bibliographical notes 62
Chapter 3 CB Processes: Extinction 65
3.1 Definition of processes and basic properties 65
3.1.1 Basic properties 69
3.1.2 Probability generating functions and moments 73
3.2 Extinction probability 75
3.2.1 Subcritical processes 76
3.2.2 Supercritical processes 78
3.2.3 Critical processes 84
3.3 Background and bibliographical notes 91
Chapter 4 CB Processes: Limit Theorems 95
4.1 Subcritical processes 95
4.2 Critical processes 100
4.2.1 Extinction is not certain 101
4.2.2 Extinction is certain 109
4.2.3 Feller diffusion approximation 110
4.3 Supercritical processes 115
4.3.1 Almost sure convergence 117
4.3.2 L1-convergence 118
4.3.3 L2-convergence 121
4.4 Background and bibliographical notes 125
Chapter 5 Statistics of CB Processes 127
5.1 Maximum likelihood estimation 127
5.1.1 MLE based on entire family tree up to nth generation 130
5.1.2 EM algorithms for incomplete data 146
5.1.3 Simulated example 152
5.2 Conditional weighted least squares estimation 158
5.2.1 Subcritical processes 159
5.2.2 Critical processes 161
5.2.3 Supercritical processes 166
5.3 Minimum disparity estimation 169
5.4 Bayesian inference 171
5.4.1 Estimation based on entire family tree up to nth generation 172
5.4.2 MCMC algorithms for incomplete data 173
5.5 Background and bibliographical notes 176
Appendices 179
Appendix 1 181
Appendix 2 185
Appendix 3 191
Appendix 4 195
Bibliography 197
Index 209
Preface xi
Chapter 1 Classical Branching Models 1
1.1 Bienaymé-Galton-Watson process 1
1.1.1 Moments and probability of extinction 4
1.1.2 Limit theorems 9
1.2 Processes with unrestricted immigration 17
1.2.1 Limit theorems 21
1.2.2 Critical process with decreasing to zero immigration 25
1.3 Processes with immigration after empty generation only 29
1.3.1 Limit theorems 31
1.3.2 Critical process with decreasing to zero immigration 36
1.4 Background and bibliographical notes 40
Chapter 2 Branching Processes with Migration 43
2.1 Galton-Watson process with migration 43
2.2 Limit theorems 47
2.2.1 Non-critical processes 47
2.2.2 Critical processes with non-negative migration mean 49
2.2.3 Critical processes with negative migration mean 52
2.3 Regeneration and migration 55
2.3.1 Alternating regenerative processes 56
2.3.2 An extension of Galton-Watson processes with migration 58
2.4 Background and bibliographical notes 62
Chapter 3 CB Processes: Extinction 65
3.1 Definition of processes and basic properties 65
3.1.1 Basic properties 69
3.1.2 Probability generating functions and moments 73
3.2 Extinction probability 75
3.2.1 Subcritical processes 76
3.2.2 Supercritical processes 78
3.2.3 Critical processes 84
3.3 Background and bibliographical notes 91
Chapter 4 CB Processes: Limit Theorems 95
4.1 Subcritical processes 95
4.2 Critical processes 100
4.2.1 Extinction is not certain 101
4.2.2 Extinction is certain 109
4.2.3 Feller diffusion approximation 110
4.3 Supercritical processes 115
4.3.1 Almost sure convergence 117
4.3.2 L1-convergence 118
4.3.3 L2-convergence 121
4.4 Background and bibliographical notes 125
Chapter 5 Statistics of CB Processes 127
5.1 Maximum likelihood estimation 127
5.1.1 MLE based on entire family tree up to nth generation 130
5.1.2 EM algorithms for incomplete data 146
5.1.3 Simulated example 152
5.2 Conditional weighted least squares estimation 158
5.2.1 Subcritical processes 159
5.2.2 Critical processes 161
5.2.3 Supercritical processes 166
5.3 Minimum disparity estimation 169
5.4 Bayesian inference 171
5.4.1 Estimation based on entire family tree up to nth generation 172
5.4.2 MCMC algorithms for incomplete data 173
5.5 Background and bibliographical notes 176
Appendices 179
Appendix 1 181
Appendix 2 185
Appendix 3 191
Appendix 4 195
Bibliography 197
Index 209
Foreword ix
Preface xi
Chapter 1 Classical Branching Models 1
1.1 Bienaymé-Galton-Watson process 1
1.1.1 Moments and probability of extinction 4
1.1.2 Limit theorems 9
1.2 Processes with unrestricted immigration 17
1.2.1 Limit theorems 21
1.2.2 Critical process with decreasing to zero immigration 25
1.3 Processes with immigration after empty generation only 29
1.3.1 Limit theorems 31
1.3.2 Critical process with decreasing to zero immigration 36
1.4 Background and bibliographical notes 40
Chapter 2 Branching Processes with Migration 43
2.1 Galton-Watson process with migration 43
2.2 Limit theorems 47
2.2.1 Non-critical processes 47
2.2.2 Critical processes with non-negative migration mean 49
2.2.3 Critical processes with negative migration mean 52
2.3 Regeneration and migration 55
2.3.1 Alternating regenerative processes 56
2.3.2 An extension of Galton-Watson processes with migration 58
2.4 Background and bibliographical notes 62
Chapter 3 CB Processes: Extinction 65
3.1 Definition of processes and basic properties 65
3.1.1 Basic properties 69
3.1.2 Probability generating functions and moments 73
3.2 Extinction probability 75
3.2.1 Subcritical processes 76
3.2.2 Supercritical processes 78
3.2.3 Critical processes 84
3.3 Background and bibliographical notes 91
Chapter 4 CB Processes: Limit Theorems 95
4.1 Subcritical processes 95
4.2 Critical processes 100
4.2.1 Extinction is not certain 101
4.2.2 Extinction is certain 109
4.2.3 Feller diffusion approximation 110
4.3 Supercritical processes 115
4.3.1 Almost sure convergence 117
4.3.2 L1-convergence 118
4.3.3 L2-convergence 121
4.4 Background and bibliographical notes 125
Chapter 5 Statistics of CB Processes 127
5.1 Maximum likelihood estimation 127
5.1.1 MLE based on entire family tree up to nth generation 130
5.1.2 EM algorithms for incomplete data 146
5.1.3 Simulated example 152
5.2 Conditional weighted least squares estimation 158
5.2.1 Subcritical processes 159
5.2.2 Critical processes 161
5.2.3 Supercritical processes 166
5.3 Minimum disparity estimation 169
5.4 Bayesian inference 171
5.4.1 Estimation based on entire family tree up to nth generation 172
5.4.2 MCMC algorithms for incomplete data 173
5.5 Background and bibliographical notes 176
Appendices 179
Appendix 1 181
Appendix 2 185
Appendix 3 191
Appendix 4 195
Bibliography 197
Index 209
Preface xi
Chapter 1 Classical Branching Models 1
1.1 Bienaymé-Galton-Watson process 1
1.1.1 Moments and probability of extinction 4
1.1.2 Limit theorems 9
1.2 Processes with unrestricted immigration 17
1.2.1 Limit theorems 21
1.2.2 Critical process with decreasing to zero immigration 25
1.3 Processes with immigration after empty generation only 29
1.3.1 Limit theorems 31
1.3.2 Critical process with decreasing to zero immigration 36
1.4 Background and bibliographical notes 40
Chapter 2 Branching Processes with Migration 43
2.1 Galton-Watson process with migration 43
2.2 Limit theorems 47
2.2.1 Non-critical processes 47
2.2.2 Critical processes with non-negative migration mean 49
2.2.3 Critical processes with negative migration mean 52
2.3 Regeneration and migration 55
2.3.1 Alternating regenerative processes 56
2.3.2 An extension of Galton-Watson processes with migration 58
2.4 Background and bibliographical notes 62
Chapter 3 CB Processes: Extinction 65
3.1 Definition of processes and basic properties 65
3.1.1 Basic properties 69
3.1.2 Probability generating functions and moments 73
3.2 Extinction probability 75
3.2.1 Subcritical processes 76
3.2.2 Supercritical processes 78
3.2.3 Critical processes 84
3.3 Background and bibliographical notes 91
Chapter 4 CB Processes: Limit Theorems 95
4.1 Subcritical processes 95
4.2 Critical processes 100
4.2.1 Extinction is not certain 101
4.2.2 Extinction is certain 109
4.2.3 Feller diffusion approximation 110
4.3 Supercritical processes 115
4.3.1 Almost sure convergence 117
4.3.2 L1-convergence 118
4.3.3 L2-convergence 121
4.4 Background and bibliographical notes 125
Chapter 5 Statistics of CB Processes 127
5.1 Maximum likelihood estimation 127
5.1.1 MLE based on entire family tree up to nth generation 130
5.1.2 EM algorithms for incomplete data 146
5.1.3 Simulated example 152
5.2 Conditional weighted least squares estimation 158
5.2.1 Subcritical processes 159
5.2.2 Critical processes 161
5.2.3 Supercritical processes 166
5.3 Minimum disparity estimation 169
5.4 Bayesian inference 171
5.4.1 Estimation based on entire family tree up to nth generation 172
5.4.2 MCMC algorithms for incomplete data 173
5.5 Background and bibliographical notes 176
Appendices 179
Appendix 1 181
Appendix 2 185
Appendix 3 191
Appendix 4 195
Bibliography 197
Index 209