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Gelman A., Carlin J.B., Stern H.S. — Bayesian data analysis
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Название: Bayesian data analysisАвторы: Gelman A., Carlin J.B., Stern H.S.Аннотация: Incorporating new and updated information, this second edition of THE bestselling text in Bayesian data analysis continues to emphasize practice over theory, describing how to conceptualize, perform, and critiques statistical analysis from a Bayesian perspective. Changes in the new edition include: added material on how Bayesian methods are connected to other approaches, stronger focus on MCMC, added chapter on further computation topics, more examples, and additional chapters on current models for Bayesian data analysis such as equation models, generalized linear mixed models, and more. The book is an introductory text and a reference for working scientists throughout their professional life.
Язык: Рубрика: Математика /Статус предметного указателя: Готов указатель с номерами страниц ed2k: ed2k stats Издание: 2nd editionГод издания: 2004Количество страниц: 668Добавлена в каталог: 11.02.2006Операции: Положить на полку |
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Dispersion parameter for generalized linear models 416 Distinct parameters and ignorability 204 distribution 573—584 Distribution, 574 580 Distribution, Bernoulli 583 Distribution, Beta 34 40 70 576 581 Distribution, beta-binomial 70 576 583 Distribution, binomial 576 583 Distribution, Cauchy 113 Distribution, Dirichlet 83 576 582 Distribution, exponential 574 580 Distribution, gamma 53 574 579 Distribution, Gaussian see "Normal distribution" Distribution, inverse- 574 580 Distribution, inverse-gamma 50 574 580 Distribution, inverse-Wishart 87 574 581 Distribution, lognormal 578 Distribution, long-tailed 444 Distribution, multinomial 576 583 Distribution, multivariate normal 95 574 578 Distribution, multivariate normal, marginals and conditionals 578 Distribution, multivariate t 315 576 Distribution, negative binomial 52 150 576 583 Distribution, normal 574 578 Distribution, normal-inverse- 78 99 Distribution, Poisson 576 582 Distribution, scaled inverse- 50 75 574 580 Distribution, standard normal 578 Distribution, Student-t 76 576 581 Distribution, uniform 573 574 Distribution, Weibull 580 Distribution, Wishart 574 581 Divorce rates 122 153 Dobra, A. 440 Dog metabolism example 387 Dominici, F. 152 Donoho, D. 66 Dose-response relation 89 Doviak, M. 31 Dransfield, M. 348 Draper, D. 28 191 Duane, S. 348 DuMouchel, W. 152 Dunsmore, I. 66 Earls, F. 411 ECM and ECME algorithms 321 322 331 Eddy, W. 190 Educational testing experiments see "SAT coaching experiments" Edwards, W. 113 237 Effective number of parameters 181—182 Effective number of parameters, educational testing example 183 Effective number of simulation draws 298 Efficiency 111 Efron, B. 150 244 255 257 332 Ehrenberg, A. 257 Eight schools see "SAT coaching experiments" Elections, forecasting Presidential elections 392—399 Elections, incumbency in U.S. Congress 359—367 Elections, pre-election polling in Slovenia 534—539 Elections, pre-election polling in U.S. 428—430 526—533 Elections, probability of a tie 30 Eltinge, J. 539 EM algorithm 317—324 EM algorithm for missing-data models 521—522 EM algorithm, AECM algorithm 322 EM algorithm, debugging 319 EM algorithm, ECM and ECME algorithms 321 322 331 EM algorithm, parameter expansion 324 331 EM algorithm, SEM and SECM algorithms 322—324 Empirical Bayes 121 Environmental health, allergen measurements 498 Environmental health, perchloroethlyene 504 Environmental health, radon 555 Ericson, W. 237 Estimands 4 26 276 Exchangeability 28 Exchangeable models 5 121—125 239 Exchangeable models and explanatory variables 6 Exchangeable models, no conflict with robustness 444 Exchangeable models, objections to 124 148 Exchangeable models, universal applicability of 123 experiments 218—226 Experiments, completely randomized 218—220 Experiments, definition 218 Experiments, distinguished from observational studies 226 Experiments, Latin square 220 Experiments, randomization 223—226 Experiments, randomized block 220 Experiments, sequential 221 244 Explanatory variables see "Regression models" Exponential distribution 574 580 Exponential families 42 Exponential model 55 71 External validation 159 External validation, record linkage example 18 External validation, toxicology example 514 Factorial analysis, internet example 409—411 Fader, P. 440 Fagan, J. 440 Fay, R. 151 Fearn, T. 411 Federalist papers 458 Feller, W. 29 308 Fienberg, S. 95 438 440 Fill, J. 348 Finite-population inference 202—203 205 207—209 211 212 216 218—221 241 Finite-population inference in ANOVA 408—409 Fisher information 107 Fisher, R. 332 514 Fixed effects 391 Fixed effects and finite-population models in ANOVA 409 Flannery, B. 331 348 584 Fluhler, H. 28 89 95 192 Football point spreads 14—17 29 30 51—52 82 Ford, E. 569 Forecasting Presidential elections 158 392—399 Forecasting Presidential elections, hierarchical model 396 Forecasting Presidential elections, problems with ordinary linear regression 394 Fowlkes, E. 29 Fox, J. 29 385 608 Frangakis, C. 238 Freedman, L. 255 Frequency evaluations 111—113 Frequentist perspective 111 Friel, N. 349 Fulkerson, W. 238 Gamma distribution 53 574 579 Garbe, P. 569 Gatsonis, C. 28 411 Gaussian distribution see "Normal distribution" Gaver, D. 457 Gebler, N. 568 Geisser, S. 190 Gelfand, A. 190 191 238 309 331 348 412 440 494 Gelman, A. 28—30 66 190—193 238 255 272 308 309 348 385 395 411 412 439 457 479 480 514 515 539 540 568 569 Geman, D. 308 Geman, S. 308 Generalized linear models 415—442 Generalized linear models, computation 421—425 Generalized linear models, hierarchical 421 Generalized linear models, hierarchical logistic regression 428—430 Generalized linear models, hierarchical Poisson regression 425—428 Generalized linear models, overdispersion 418 439 441 Generalized linear models, prior distribution 420—421 Generalized linear models, simple logistic regression example 88—93 Genetics 9 30 Genovese, C. 515 Geometric mean (GM) 7 Geometric standard deviation (GSD) 7 George, E. 191 412 515 Geweke, J. 348 Geyer, C. 348 349 Ghosh, S. 191 Gibbs sampler 287—289 292 294 308—309 Gibbs sampler for separation model of covariance matrices 484 Gibbs sampler, all-at-once for hierarchical regression 402 Gibbs sampler, blockwise for hierarchical regression 401 Gibbs sampler, efficiency 302—305 Gibbs sampler, examples 300 380 449 474 538 Gibbs sampler, hierarchical linear models 299—302 400—405 407—408 Gibbs sampler, linear transformation for hierarchical regression 403 Gibbs sampler, parameter expansion for hierarchical regression 404 407 Gibbs sampler, picture of 288 Gibbs sampler, programming in R 601—608 Gibbs sampler, scalar for hierarchical regression 402 Gibbs sampler, special case of Metropolis — Hastings algorithm 293 Gilks, W. 29 113 151 191 308 309 439 608 Gill, J. 27 Gill, P. 331 385 Gilovich, T. 568 Giltinan, D. 514 Girl births, proportion of 43—46 Giudici, P. 309 348 Glickman, M. 29 239 309 411 440 Global mode, why it is not special 312 GM, geometric mean 7 Goegebeur, Y. 439 Goldman, L. 238 Goldstein, H. 238 411 Goldstein, M. 412 Golf putting, nonlinear model for 515 Golub, G. 385 Good, I. 28 95 150 440 Goodman, L. 68 440 Goodman, S. 255 Goodness-of-fit testing 250 see Graphical models 151 Graphical posterior predictive checks 165—172 Graphics, examples of use in model checking 159 160 166—170 Graphics, jittering 15 16 29 Graphics, posterior predictive checks 165—172 Green, P. 309 348 480 Greenberg, E. 308 Greenland, S. 237 Grenander, U. 494 Grid approximation 91—92 284 Grieve, A. 28 89 95 192 Griffin, D. 568 Griffiths, G. 255 Groves, R. 539 568 GSD, geometric standard deviation 7 Gull, s. 66 387 Guttman, I. 190 Hamiltonian (hybrid) MCMC 335—336 348 Hammersley, J. 308 348 Handscomb, D. 308 348 Hansen, M. 191 Harrell, F. 238 Harris, J. 152 Harrison, J. 494 Hartigan, J. 66 Hartley, H. 150 Harville, D. 29 Hasselblad, V. 152 Hastie, T. 191 255 Hastings, W. 308 Heckman, J. 238 Heitjan, D. 96 238 539 569 Henderson, C. 411 Herriot, R. 151 Heteroscedasticity in linear regression 372—382 Heteroscedasticity in linear regression, parametric model for 376 Hierarchical linear regression 389—414 Hierarchical linear regression, computation 400—405 407—408 Hierarchical linear regression, interpretation as a single linear regression 399 Hierarchical logistic regression 428—430 Hierarchical models 6 117—156 389—414 Hierarchical models, analysis of variance (ANOVA) 406 Hierarchical models, binomial 127—131 155 Hierarchical models, bivariate normal 212—214 Hierarchical models, business school grades 486—488 Hierarchical models, cluster sampling 214—216 Hierarchical models, computation 125—131 Hierarchical models, forecasting elections 392—399 Hierarchical models, logistic regression 428—430 Hierarchical models, many batches of random effects election forecasting example 396 Hierarchical models, many batches of random effects election forecasting example, polling example 428—430 Hierarchical models, meta-analysis 145—150 488—491 Hierarchical models, multivariate 486—491 526—533 Hierarchical models, no unique way to set up 400 Hierarchical models, normal 131—150 299—302 325—331 Hierarchical models, NYPD stops 425—428 Hierarchical models, pharmacokinetics example 260 Hierarchical models, Poisson 155 425—428 Hierarchical models, pre-election polling 212—214 Hierarchical models, prediction 125 137 Hierarchical models, prior distribution see "Hyperprior distribution" Hierarchical models, radon 555—567 Hierarchical models, rat tumor example 127—131 Hierarchical models, SAT coaching 138—145 Hierarchical models, schizophrenia example 468—479 Hierarchical models, stratified sampling 212—214 Hierarchical models, survey incentives 544—552 Hierarchical Poisson regression 425—428 Hierarchical regression 389—414 Hierarchical regression, an alternative to selecting regression variables 405—406 Hierarchical regression, prediction 397 Higdon, D. 309 348 494 Higgins, K. 514 Highest posterior density interval 38 Hill, B. 151 Hill, J. 238 Hills, S. 309 Hinde, J. 439 441 Hinkley, D. 195 255 Hirano, K. 238 Hoadley, B. 29 Hoch, J. 66 Hodges, J. 28 191 412 413 Hoerl, A. 412 Hoeting, J. 191 Hogan, H. 29 Holmes, C. 515 Holt, D. 238 Hornbuckle, J. 255 Hsu, J. 493 Huang, Z. 385 412 Hui, S. 411 Hunter, C. 30 Hunter, J. 309 Hunter, W. 309 Hybrid MCMC 335—336 348 Hyperparameter 40 117 122 Hyperprior distribution 124—125 Hyperprior distribution, informative 260 Hyperprior distribution, noninformative 125 127—129 134 136 137 154 470 489 Hypothesis testing 162 175 180 250 Ibrahim, J. 191 308 Identifiability 369 Ignorability 203—207 239 518 Ignorability, incumbency example 361 Ignorability, strong 205 Ignorable and known designs 205 Ignorable and known designs given covariates 205 Ignorable and unknown designs 206 Iid (independent and identically distributed) 6 Ill-posed systems, differential equation model in toxicology 504—514 Ill-posed systems, mixture of exponentials 516 Imai, K. 440 Imbens, G. 238 245
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