Practical nonparametric and semiparametric Bayesian statistics:
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
New York [u.a.]
Springer
1998
|
| Schriftenreihe: | Lecture notes in statistics
133 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XVI, 369 S. graph. Darst. |
| ISBN: | 0387985174 |
Internformat
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Datensatz im Suchindex
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| adam_text | DIPAK DEY PETER MUELLER DEBAJYOTI SINHA (EDITORS) PRACTICAL NONPARAMETRIC
AND SEMIPARAMETRIC BAYESIAN STATISTICS SPRINGER CONTENTS I DIRICHLET AND
RELATED PROCESSES 1 COMPUTING NONPARAMETRIC HIERARCHICAL MODELS 1 M. D.
ESCOBAR AND M. WEST 1.1 INTRODUCTION 1 1.2 NOTATION AND PERSPECTIVES 3
1.3 POSTERIOR SAMPLING IN DIRICHLET PROCESS MIXTURES 5 1.4 AN EXAMPLE
WITH POISSON-GAMMA STRUCTURE 12 1.5 AN EXAMPLE WITH NORMAL STRUCTURE 16
2 COMPUTATIONAL METHODS FOR MIXTURE OF DIRICHLET PROCESS MODELS 23 S. N.
MACEACHERN 2.1 INTRODUCTION 23 2.2 THE BASIC ALGORITHM 26 2.3 MORE
EFFICIENT ALGORITHMS 27 2.4 NON-CONJUGATE MODELS 39 2.5 DISCUSSION 40 3
NONPARAMETRIC BAYES METHODS USING PREDICTIVE UPDATING 45 M. A. NEWTON,
F.A. QUINTANA, AND Y. ZHANG 3.1 INTRODUCTION 45 3.2 ON N = 1 46 3.3 A
RECURSIVE ALGORITHM 47 3.4 INTERVAL CENSORING 48 3.5 CENSORING EXAMPLE
50 3.6 MIXING EXAMPLE 54 3.7 ONN = 2 57 3.8 CONCLUDING REMARKS 58 4
DYNAMIC DISPLAY OF CHANGING POSTERIOR IN BAYESIAN SURVIVAL ANALYSIS 63
H. DOSS AND B. NARASIMHAN 4.1 INTRODUCTION AND SUMMARY 63 4.2 A GIBBS
SAMPLER FOR CENSORED DATA 65 4.3 PROOF OF PROPOSITION 1 67 4.4
IMPORTANCE SAMPLING 70 X CONTENTS 4.5 THE ENVIRONMENT FOR DYNAMIC
GRAPHICS 75 4.6 APPENDIX: COMPLETION OF THE PROOF OF PROPOSITION 1 . . .
. 84 5 SEMIPARAMETRIC BAYESIAN METHODS FOR RANDOM EFFECTS MODELS 89 J.
G. IBRAHIM AND K. P. KLEINMAN 5.1 INTRODUCTION 89 5.2 NORMAL LINEAR
RANDOM EFFECTS MODELS 91 5.3 DP PRIORS IN THE NORMAL LINEAR RANDOM
EFFECTS MODEL . . 91 5.4 GENERALIZED LINEAR MIXED MODELS 97 5.5 DP
PRIORS IN THE GENERALIZED LINEAR MIXED MODEL 99 5.6 APPLICATIONS 101 5.7
DISCUSSION 112 6 NONPARAMETRIC BAYESIAN GROUP SEQUENTIAL DESIGN 115 P.
K. VLACHOS AND A. E. GELFAND 6.1 INTRODUCTION 115 6.2 THE DP MIXING
APPROACH APPLIED TO THE GROUP SEQUENTIAL FRAMEWORK 117 6.3 MODEL FITTING
TECHNIQUES 119 6.4 IMPLEMENTATION OF THE DESIGN 121 6.5 EXAMPLES 122 II
MODELING RANDOM FUNCTIONS 7 WAVELET-BASED NONPARAMETRIC BAYES METHODS
133 B. VIDAKOVIC 7.1 INTRODUCTION 133 7.2 DISCRETE WAVELET
TRANSFORMATIONS 135 7.3 BAYES AND WAVELETS 136 7.4 OTHER PROBLEMS 150 8
NONPARAMETRIC ESTIMATION OF IRREGULAER FUNCTIONS WITH INDEPENDENT OR
AUTOCORRELATED ERRORS 157 M. SMITH AND R. KOHN 8.1 INTRODUCTION 157 8.2
NONPARAMETRIC REGRESSION FOR INDEPENDENT ERRORS 159 8.3 NONPARAMETRIC
REGRESSION FOR DATA WITH AUTOCORRELATED ERRORS 171 9 FEEDFORWARD NEURAL
NETWORKS FOR NONPARAMETRIC REGRESSION 181 D. RIOS INSUA AND P. MUELLER
9.1 INTRODUCTION 181 * CONTENTS XI 9.2 FEED FORWARD NEURAL NETWORKS AS
NONPARAMETRIC REGRESSION MODELS 182 9.3 VARIABLE ARCHITECTURE FFNNS 183
9.4 POSTERIOR INFERENCE WITH THE FFNN MODEL 185 9.5 EXAMPLES 189 9.6
DISCUSSION 191 III LEVY AND RELATED PROCESSES 10 SURVIVAL ANALYSIS USING
SEMIPARAMETRIC BAYESIAN METHODS 195 D. SINHA AND D. DEY 10.1
INTRODUCTION 195 10.2 MODELS 197 10.3 PRIOR PROCESSES 199 10.4 BAYESIAN
ANALYSIS 201 10.5 FURTHER READINGS 207 11 BAYESIAN NONPARAMETRIC AND
COVARIATE ANALYSIS OF FAILURE TIME DATA 213 P.W. LAUD, P. DAMIEN, AND
A.F.M. SMITH 11.1 INTRODUCTION 213 11.2 COX MODEL WITH BETA PROCESS
PRIOR 214 11.3 THE COMPUTATIONAL MODEL 216 11.4 ILLUSTRATIVE ANALYSIS
217 11.5 CONCLUSION 220 12 SIMULATION OF LEVY RANDOM FIELDS 227 R.L.
WOLPERT AND K. ICKSTADT 12.1 INTRODUCTION AND OVERVIEW 227 12.2
INCREASING INDEPENDENT-INCREMENT PROCESSES: A NEW LOOK AT AN OLD IDEA
228 12.3 EXAMPLE: GAMMA VARIATES, PROCESSES, AND FIELDS 229 12.4
INHOMOGENEOUS LEVY RANDOM FIELDS 233 12.5 COMPARISONS WITH OTHER METHODS
236 12.6 CONCLUSIONS 238 13 SAMPLING METHODS FOR BAYESIAN NONPARAMETRIC
INFERENCE INVOLVING STOCHASTIC PROCESSES 243 S. WALKER AND P. DAMIEN
13.1 INTRODUCTION 243 13.2 NEUTRAL TO THE RIGHT PROCESSES 244 13.3
MIXTURES OF DIRICHLET PROCESSES 247 13.4 CONCLUSIONS 252 XII CONTENTS 14
CURVE AND SURFACE ESTIMATION USING DYNAMIC STEP FUNCTIONS 255 J.
HEIKKINEN 14.1 INTRODUCTION 255 14.2 SOME STATISTICAL PROBLEMS 257 14.3
SOME SPATIAL STATISTICS 258 14.4 PROTOTYPE PRIOR 260 14.5 POSTERIOR
INFERENCE 262 14.6 EXAMPLE IN INTENSITY ESTIMATION 264 14.7 DISCUSSION
264 IV PRIOR ELICITATION AND ASYMPTOTIC PROPERTIES 15 PRIOR ELICITATION
FOR SEMIPARAMETRIC BAYESIAN SURVIVAL ANALYSIS 273 J. G. IBRAHIM AND D.
SINHA 15.1 INTRODUCTION 273 15.2 THE METHOD 275 15.3 SAMPLING FROM THE
JOINT POSTERIOR DISTRIBUTION OF (/?, A,A 0 ) 281 15.4 APPLICATIONS TO
VARIABLE SELECTION 284 15.5 MYELOMADATA 288 15.6 DISCUSSION 290 16
ASYMPTOTIC PROPERTIES OF NONPARAMETRIC BAYESIAN PROCEDURES 293 L.
WASSERMAN 16.1 INTRODUCTION 293 16.2 FREQUENTIST OR BAYESIAN
ASYMPTOTICS? 294 16.3 CONSISTENCY 294 16.4 CONSISTENCY IN HELLINGER
DISTANCE 296 16.5 OTHER ASYMPTOTIC PROPERTIES 299 16.6 THE ROBINS-RITOV
PARADOX 301 16.7 CONCLUSION 302 V CASE STUDIES 305 17 MODELING TRAVEL
DEMAND IN PORTLAND, OREGON 305 K. ICKSTADT, R.L. WOLPERT, AND X. LU 17.1
INTRODUCTION 305 17.2 THE DATA 307 17.3 POISSON/GAMMA RANDOM FIELD
MODELS 310 17.4 THE COMPUTATIONAL SCHEME 312 CONTENTS XIII 17.5
POSTERIOR ANALYSIS 315 17.6 DISCUSSION 319 18 SEMIPARAMETRIC PK/PD
MODELS 323 P. MUELLER AND G. ROSNER 18.1 INTRODUCTION 323 18.2 A
SEMIPARAMETRIC POPULATION MODEL 327 18.3 META-ANALYSIS OVER RELATED
STUDIES 331 18.4 DISCUSSION 335 19 A BAYESIAN MODEL FOR FATIGUE CRACK
GROWTH 339 L. LIU AND E. ARJAS 19.1 INTRODUCTION 339 19.2 THE MODEL 340
19.3 A MARKOV CHAIN MONTE CARLO METHOD 342 19.4 AN EXAMPLE: GROWTH OF
CRACK LENGTHS 345 19.5 DISCUSSION 350 20 A SEMIPARAMETRIC MODEL FOR
LABOR EARNINGS DYNAMICS 355 K. HIRANO 20.1 INTRODUCTION 355 20.2
LONGITUDINAL EARNINGS DATA 357 20.3 A PARAMETRIC RANDOM EFFECTS MODEL
358 20.4 A SEMIPARAMETRIC MODEL 360 20.5 PREDICTIVE DISTRIBUTIONS 362
20.6 CONCLUSION 367
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| id | DE-604.BV012038487 |
| illustrated | Illustrated |
| indexdate | 2024-07-09T18:20:33Z |
| institution | BVB |
| isbn | 0387985174 |
| language | English |
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| publishDate | 1998 |
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| series | Lecture notes in statistics |
| series2 | Lecture notes in statistics |
| spelling | Practical nonparametric and semiparametric Bayesian statistics Dipak Dey ... (eds.) New York [u.a.] Springer 1998 XVI, 369 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Lecture notes in statistics 133 Besliskunde gtt Inferencia nao parametrica larpcal Methode van Bayes gtt Non-parametrische statistiek gtt Statistique bayésienne Statistique non paramétrique Bayesian statistical decision theory Nonparametric statistics Nichtparametrisches Verfahren (DE-588)4339273-8 gnd rswk-swf Bayes-Entscheidungstheorie (DE-588)4144220-9 gnd rswk-swf Semiparametrisches Modell (DE-588)4232479-8 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content Bayes-Entscheidungstheorie (DE-588)4144220-9 s Nichtparametrisches Verfahren (DE-588)4339273-8 s DE-604 Semiparametrisches Modell (DE-588)4232479-8 s Dey, Dipak 1953- Sonstige (DE-588)124746306 oth Lecture notes in statistics 133 (DE-604)BV002447846 133 GBV Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=008146354&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Practical nonparametric and semiparametric Bayesian statistics Lecture notes in statistics Besliskunde gtt Inferencia nao parametrica larpcal Methode van Bayes gtt Non-parametrische statistiek gtt Statistique bayésienne Statistique non paramétrique Bayesian statistical decision theory Nonparametric statistics Nichtparametrisches Verfahren (DE-588)4339273-8 gnd Bayes-Entscheidungstheorie (DE-588)4144220-9 gnd Semiparametrisches Modell (DE-588)4232479-8 gnd |
| subject_GND | (DE-588)4339273-8 (DE-588)4144220-9 (DE-588)4232479-8 (DE-588)4143413-4 |
| title | Practical nonparametric and semiparametric Bayesian statistics |
| title_auth | Practical nonparametric and semiparametric Bayesian statistics |
| title_exact_search | Practical nonparametric and semiparametric Bayesian statistics |
| title_full | Practical nonparametric and semiparametric Bayesian statistics Dipak Dey ... (eds.) |
| title_fullStr | Practical nonparametric and semiparametric Bayesian statistics Dipak Dey ... (eds.) |
| title_full_unstemmed | Practical nonparametric and semiparametric Bayesian statistics Dipak Dey ... (eds.) |
| title_short | Practical nonparametric and semiparametric Bayesian statistics |
| title_sort | practical nonparametric and semiparametric bayesian statistics |
| topic | Besliskunde gtt Inferencia nao parametrica larpcal Methode van Bayes gtt Non-parametrische statistiek gtt Statistique bayésienne Statistique non paramétrique Bayesian statistical decision theory Nonparametric statistics Nichtparametrisches Verfahren (DE-588)4339273-8 gnd Bayes-Entscheidungstheorie (DE-588)4144220-9 gnd Semiparametrisches Modell (DE-588)4232479-8 gnd |
| topic_facet | Besliskunde Inferencia nao parametrica Methode van Bayes Non-parametrische statistiek Statistique bayésienne Statistique non paramétrique Bayesian statistical decision theory Nonparametric statistics Nichtparametrisches Verfahren Bayes-Entscheidungstheorie Semiparametrisches Modell Aufsatzsammlung |
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