000 05270cam a2200397 i 4500
005 20211105021538.0
008 100426s2010 flua b 001 0 eng d
010 _a 2009026637
011 _aBIB MATCHES WORLDCAT
020 _a1439811873
_qhardcover (alk. paper)
020 _a9781439811870
_qhardcover (alk. paper)
035 _a(ATU)b11674921
035 _a(OCoLC)301889402
040 _aDLC
_beng
_erda
_cDLC
_dBTCTA
_dYDXCP
_dC#P
_dUKM
_dCDX
_dATU
050 0 0 _aQH352
_b.B38 2010
082 0 0 _a577.8801519542
_222
100 1 _aKing, Ruth,
_d1977-
_eauthor.
_9448513
245 1 0 _aBayesian analysis for population ecology /
_cRuth King [and others].
264 1 _aBoca Raton :
_bChapman & Hall/CRC,
_c[2010]
264 4 _c©2010
300 _axiii, 442 pages :
_billustrations ;
_c25 cm.
336 _atext
_btxt
_2rdacontent
337 _aunmediated
_bn
_2rdamedia
338 _avolume
_bnc
_2rdacarrier
490 1 _aInterdisciplinary statistics series
504 _aIncludes bibliographical references and index.
505 0 0 _gPart I.
_tIntroduction to Statistical Analysis of Ecological Data --
_g1.
_tIntroduction --
_g1.1.
_tPopulation Ecology --
_g1.2.
_tConservation and Management --
_g1.3.
_tData and Models --
_g1.4.
_tBayesian and Classical Statistical Inference --
_g1.5.
_tSenescence --
_g1.6.
_tSummary --
_g1.7.
_tFurther Reading --
_g1.8.
_tExercises --
_g2.
_tData, Models and Likelihoods --
_g2.1.
_tIntroduction --
_g2.2.
_tPopulation Data --
_g2.3.
_tModelling Survival --
_g2.4.
_tMulti-Site, Multi-State and Movement Data --
_g2.5.
_tCovariates and Large Data Sets --
_g2.6.
_tCombining Information --
_g2.7.
_tModelling Productivity --
_g2.8.
_tParameter Redundancy --
_g2.9.
_tSummary --
_g2.10.
_tFurther Reading --
_g2.11.
_tExercises --
_g3.
_tClassical Inference Based on Likelihood --
_g3.1.
_tIntroduction --
_g3.2.
_tSimple Likelihoods --
_g3.3.
_tModel Selection --
_g3.4.
_tMaximising Log-Likelihoods --
_g3.5.
_tConfidence Regions --
_g3.6.
_tComputer Packages --
_g3.7.
_tSummary --
_g3.8.
_tFurther Reading --
_g3.9.
_tExercises --
_gPart II.
_tBayesian Techniques and Tools --
_g4.
_tBayesian Inference --
_g4.1.
_tIntroduction --
_g4.2.
_tPrior Selection and Elicitation --
_g4.3.
_tPrior Sensitivity Analyses --
_g4.4.
_tSummarising Posterior Distributions --
_g4.5.
_tDirected Acyclic Graphs --
_g4.6.
_tSummary --
_g4.7.
_tFurther Reading --
_g4.8.
_tExercises --
_g5.
_tMarkov Chain Monte Carlo --
_g5.1.
_tMonte Carlo Integration --
_g5.2.
_tMarkov Chains --
_g5.3.
_tMarkov Chain Monte Carlo --
_g5.4.
_tImplementing MCMC --
_g5.5.
_tSummary --
_g5.6.
_tFurther Reading --
_g5.7.
_tExercises --
_g6.
_tModel Discrimination --
_g6.1.
_tIntroduction --
_g6.2.
_tBayesian Model Discrimination --
_g6.3.
_tEstimating Posterior Model Probabilities --
_g6.4.
_tPrior Sensitivity --
_g6.5.
_tModel Averaging --
_g6.6.
_tMarginalPosterior Distributions --
_g6.7.
_tAssessing Temporal /Age Dependence --
_g6.8.
_tImproving and Checking Performance --
_g6.9.
_tAdditional Computational Techniques --
_g6.10.
_tSummary --
_g6.11.
_tFurther Reading --
_g6.12.
_tExercises --
_g7.
_tMCMC and RJMCMC Computer Programs --
_g7.1.
_tR Code (MCMC) for Dipper Data --
_g7.2.
_tWinBUGS Code (MCMC) for Dipper Data --
_g7.3.
_tMCMC within the Computer Package MARK --
_g7.4.
_tR code (RJMCMC) for Model Uncertainty --
_g7.5.
_tWinBUGS Code (RJMCMC) for Model Uncertainty --
_g7.6.
_tSummary --
_g7.7.
_tFurther Reading --
_g7.8.
_tExercises --
_gPart III.
_tEcological Applications --
_g8.
_tCovariates, Missing Values and Random Effects --
_g8.1.
_tIntroduction --
_g8.2.
_tCovariates --
_g8.3.
_tMissing Values --
_g8.4.
_tAssessing Covariate Dependence --
_g8.5.
_tRandom Effects --
_g8.6.
_tPrediction --
_g8.7.
_tSplines --
_g8.8.
_tSummary --
_g8.9.
_tFurther Reading --
_g9.
_tMulti-State Models --
_g9.1.
_tIntroduction --
_g9.2.
_tMissing Covariate /Auxiliary Variable Approach --
_g9.3.
_tModel Discrimination and Averaging --
_g9.4.
_tSummary --
_g9.5.
_tFurther Reading --
_g10.
_tState-Space Modelling --
_g10.1.
_tIntroduction --
_g10.2.
_tLeslie Matrix-Based Models --
_g10.3.
_tNon-Leslie-Based Models --
_g10.4.
_tCapture-Recapture Data --
_g10.5.
_tSummary --
_g10.6.
_tFurther Reading --
_g11.
_tClosed Populations --
_g11.1.
_tIntroduction --
_g11.2.
_tModels and Notation --
_g11.3.
_tModel Fitting --
_g11.4.
_tModel Discrimination and Averaging --
_g11.5.
_tLine Transects --
_g11.6.
_tSummary --
_g11.7.
_tFurther Reading --
_gAppendix A.
_tCommon Distributions --
_gAppendix A.1.
_tDiscrete Distributions --
_gAppendix A.2.
_tContinuous Distributions --
_gAppendix B.
_tProgramming in R --
_gAppendix B.1.
_tGetting Started in R --
_gAppendix B.2.
_tUseful R Commands --
_gAppendix B.3.
_tWriting (RJ)MCMC Functions --
_gAppendix B.4.
_tR Code for Model C /C --
_gAppendix B.5.
_tR Code for White Stork Covariate Analysis --
_gAppendix B.6.
_tSummary --
_gAppendix C.
_tProgramming in WinBUGS --
_gAppendix C.1.
_tWinBUGS --
_gAppendix C.2.
_tCalling WinBUGS from R --
_gAppendix C.3.
_tSummary.
588 _aMachine converted from AACR2 source record.
650 0 _aPopulation biology
_xMathematics
_9728229
650 0 _aBayesian field theory
_9340099
830 0 _aInterdisciplinary statistics.
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