Bayesian analysis for population ecology:
Saved in:
| Format: | Book |
|---|---|
| Language: | English |
| Published: |
Boca Raton
Chapman & Hall
2010
|
| Series: | Chapman & Hall/CRC interdisciplinary statistics series
|
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Item Description: | Includes bibliographical references and index |
| Physical Description: | XIII, 442 S. Ill. |
| ISBN: | 9781439811870 |
Staff View
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Record in the Search Index
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| adam_text | CHAPMAN & HALL/CRC INTERDISCIPLINARY STATISTICS SERIES BAYESIAN ANALYSIS
FOR POPULATION ECOLOGY RUTH KING BYRON J.T. MORGAN OLIVIER GIMENEZ
STEPHEN P. BROOKS CRC PRESS TAYLOR & FRANCIS CROUP BOCA RATON LONDON NEW
YORK CRC PRESS IS AN IMPRINT OF THE TAYLOR & FRANCIS GROUP, AN INFORMA
BUSINESS A CHAPMAN & HALL BOOK CONTENTS ACKNOWLEDGMENTS XI PREFACE
XIII I INTRODUCTION TO STATISTICAL ANALYSIS OF ECOLOGICAL DATA 1 1
INTRODUCTION 3 1.1 POPULATION ECOLOGY 3 1.2 CONSERVATION AND MANAGEMENT
3 1.3 DATA AND MODELS 4 1.4 BAYESIAN AND CLASSICAL STATISTICAL INFERENCE
6 1.5 SENESCENCE 9 1.6 SUMMARY 11 1.7 FURTHER READING 11 1.8 EXERCISES
12 2 DATA, MODELS AND LIKELIHOODS 15 2.1 INTRODUCTION 15 2.2 POPULATION
DATA 15 2.3 MODELLING SURVIVAL 21 2.4 MULTI-SITE, MULTI-STATE AND
MOVEMENT DATA 28 2.5 COVARIATES AND LARGE DATA SETS; SENESCENCE 30 2.6
COMBINING INFORMATION 33 2.7 MODELLING PRODUCTIVITY 35 2.8 PARAMETER
REDUNDANCY 36 2.9 SUMMARY 40 2.10 FURTHER READING 40 2.11 EXERCISES 42 3
CLASSICAL INFERENCE BASED ON LIKELIHOOD 49 3.1 INTRODUCTION 49 3.2
SIMPLE LIKELIHOODS 49 3.3 MODEL SELECTION 51 3.4 MAXIMISING
LOG-LIKELIHOODS 56 3.5 CONFIDENCE REGIONS 57 VIII CONTENTS 3.6 COMPUTER
PACKAGES 58 3.7 SUMMARY 61 3.8 FURTHER READING 62 3.9 EXERCISES 62 II
BAYESIAN TECHNIQUES AND TOOLS . 67 4 BAYESIAN INFERENCE 69 4.1
INTRODUCTION 69 4.2 PRIOR SELECTION AND ELICITATION 75 4.3 PRIOR
SENSITIVITY ANALYSES 80 4.4 SUMMARISING POSTERIOR DISTRIBUTIONS 85 4.5
DIRECTED ACYCLIC GRAPHS 89 4.6 SUMMARY 93 4.7 FURTHER READING 95 4.8
EXERCISES 96 5 MARKOV CHAIN MONTE CARLO 99 5.1 MONTE CARLO INTEGRATION
99 5.2 MARKOV CHAINS 101 5.3 MARKOV CHAIN MONTE CARLO 101 5.4
IMPLEMENTING MCMC 124 5.5 SUMMARY 141 5.6 FURTHER READING * 141 5.7
EXERCISES 142 6 MODEL DISCRIMINATION 147 6.1 INTRODUCTION 147 6.2
BAYESIAN MODEL DISCRIMINATION 148 6.3 ESTIMATING POSTERIOR MODEL
PROBABILITIES 152 6.4 PRIOR SENSITIVITY 170 6.5 MODEL AVERAGING 172 6.6
MARGINAL POSTERIOR DISTRIBUTIONS 176 6.7 ASSESSING TEMPORAL/AGE
DEPENDENCE 178 6.8 IMPROVING AND CHECKING PERFORMANCE 189 6.9 ADDITIONAL
COMPUTATIONAL TECHNIQUES 192 6.10 SUMMARY 193 6.11 FURTHER READING 194
6.12 EXERCISES 195 7 MCMC AND RJMCMC COMPUTER PROGRAMS 199 7.1 R CODE
(MCMC) FOR DIPPER DATA 199 7.2 WINBUGS CODE (MCMC) FOR DIPPER DATA 205
7.3 MCMC WITHIN THE COMPUTER PACKAGE MARK 209 CONTENTS 7.4 7.5 7.6 7.7
7.8 R CODE (RJMCMC) FOR MODEL WINBUGS CODE (RJMCMC) SUMMARY FURTHER
READING EXERCISES UNCERTAINTY FOR MODEL UNCERTAINTY IX 213 226 231 232
233 8.1 8.2 8.3 8.4 8.5 8.6 8.7 8.8 8.9 INTRODUCTION COVARIATES MISSING
VALUES ASSESSING COVARIATE DEPENDENCE RANDOM EFFECTS PREDICTION SPLINES
SUMMARY FURTHER READING MULTI-STATE MODELS 9.1 9.2 9.3 9.4 9.5
INTRODUCTION MISSING COVARIATE/AUXILIARY VARIABLE APPROACH MODEL
DISCRIMINATION AND AVERAGING SUMMARY FURTHER READING III ECOLOGICAL
APPLICATIONS 239 8 COVARIATES, MISSING VALUES AND RANDOM EFFECTS 241 241
242 251 259 264 270 270 273 274 277 277 277 286 303 304 10 STATE-SPACE
MODELLING 307 10.1 INTRODUCTION 307 10.2 LESLIE MATRIX-BASED MODELS 314
10.3 NON-LESLIE-BASED MODELS 332 10.4 CAPTURE-RECAPTURE DATA 339 10.5
SUMMARY 342 10.6 FURTHER READING 342 11 CLOSED POPULATIONS 345 11.1
INTRODUCTION 345 11.2 MODELS AND NOTATION 346 11.3 MODEL FITTING 347
11.4 MODEL DISCRIMINATION AND AVERAGING 354 11.5 LINE TRANSECTS 356 11.6
SUMMARY 359 11.7 FURTHER READING 360 APPENDICES 363 X CONTENTS A COMMON
DISTRIBUTIONS 365 A.I DISCRETE DISTRIBUTIONS 365 A.2 CONTINUOUS
DISTRIBUTIONS 368 B PROGRAMMING IN R 375 B.I GETTING STARTED IN R 375
B.2 USEFUL R COMMANDS 376 B.3 WRITING (RJ)MCMC FUNCTIONS 378 B.4 R CODE
FOR MODEL C/C 379 B.5 R CODE FOR WHITE STORK COVARIATE ANALYSIS 387 B.6
SUMMARY 398 C PROGRAMMING IN WINBUGS 401 C.I WINBUGS 401 C.2 CALLING
WINBUGS FROM R 410 C.3 SUMMARY 415 REFERENCES 417 INDEX 435
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| isbn | 9781439811870 |
| language | English |
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| physical | XIII, 442 S. Ill. |
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| spelling | Bayesian analysis for population ecology Ruth King ... Boca Raton Chapman & Hall 2010 XIII, 442 S. Ill. txt rdacontent n rdamedia nc rdacarrier Chapman & Hall/CRC interdisciplinary statistics series Includes bibliographical references and index Mathematik Population biology Mathematics Bayesian field theory King, Ruth Sonstige oth HEBIS Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018804625&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Bayesian analysis for population ecology Mathematik Population biology Mathematics Bayesian field theory |
| title | Bayesian analysis for population ecology |
| title_auth | Bayesian analysis for population ecology |
| title_exact_search | Bayesian analysis for population ecology |
| title_full | Bayesian analysis for population ecology Ruth King ... |
| title_fullStr | Bayesian analysis for population ecology Ruth King ... |
| title_full_unstemmed | Bayesian analysis for population ecology Ruth King ... |
| title_short | Bayesian analysis for population ecology |
| title_sort | bayesian analysis for population ecology |
| topic | Mathematik Population biology Mathematics Bayesian field theory |
| topic_facet | Mathematik Population biology Mathematics Bayesian field theory |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=018804625&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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