MARC Record from harvard_bibliographic_metadata

LEADER: 03286cam a2200517 a 4500
001 013868708-0
005 20131213105336.0
008 020516s2002 enka b 001 0 eng
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040 $aUKM$beng$cUKM$dDLC$dC#P$dBAKER$dNLGGC$dBTCTA$dLVB$dYDXCP$dDEBBG$dEXW$dOCLCQ$dOCLCF$dOCLCO
042 $alccopycat
050 00 $aQA279.5$b.B388 2002
082 04 $a519.542$221
084 $a31.73$2bcl
084 $aMAT 628f$2stub
084 $aQH 233$2rvk
084 $aSK 830$2rvk
245 00 $aBayesian methods for nonlinear classification and regression /$cDavid G.T. Denison ... [et al.].
260 $aChichester, England ;$aNew York, NY :$bWiley,$cc2002.
300 $a277 p. :$bill. ;$c24 cm.
490 0 $aWiley series in probability and statistics
504 $aIncludes bibliographical references and index.
505 00 $tRegression and Classification --$tBayesian Nonlinear Methods --$tApproximating functions --$tThe 'best' model --$tBayesian methods --$tBayesian Modelling --$tData Modelling --$tThe representation theorem for classification --$tThe general representation theorem --$tBayes' Theorem --$tModelling with predictors --$tBasics of Regression Modelling --$tThe regression problem --$tBasis function models for the regression function --$tThe Bayesian Linear Model --$tThe priors --$tThe likelihood --$tThe posterior --$tModel Comparison --$tBayes' factors --$tOccam's razor --$tLindley's paradox --$tModel Selection --$tSearching for models --$tModel Averaging --$tPredictive inference --$tProblems with model selection --$tPosterior Sampling --$tThe Gibbs sampler --$tThe Metropolis-Hastings algorithm --$tThe reversible jump algorithm --$tHybrid sampling --$tConvergence --$tCurve Fitting --$tCurve Fitting Using Step Functions --$tExample: Nile discharge data --$tCurve Fitting with Splines --$tMetropolis-Hastings sampler --$tGibbs sampling --$tExample: Great Barrier Reef Data --$tMonitoring convergence of the sampler --$tDefault curve fitting --$tCurve Fitting Using Wavelets --$tWavelet shrinkage --$tBayesian wavelets --$tPrior Elicitation --$tThe model prior --$tPrior on the model parameters --$tThe prior on the coefficients --$tThe prior on the regression variance --$tRobust Curve Fitting --$tModelling with a heavy-tailed error distribution --$tOutlier detection models --$tSurface Fitting --$tAdditive Models --$tIntroduction to additive modelling --$tOzone data example.
650 0 $aBayesian statistical decision theory.
650 0 $aNonparametric statistics.
650 0 $aRegression analysis.
650 17 $aMethode van Bayes.$2gtt
650 17 $aClassificatie.$2gtt
650 17 $aNiet-lineaire modellen.$2gtt
650 17 $aRegressieanalyse.$2gtt
650 6 $aStatistique bayésienne.
650 6 $aStatistique non paramétrique.
650 6 $aAnalyse de régression.
650 07 $aBayes-Verfahren.$2swd
650 07 $aNichtlineare Regression.$2swd
650 7 $aBayesian statistical decision theory.$2fast
650 7 $aNonparametric statistics.$2fast
650 7 $aRegression analysis.$2fast
700 1 $aDenison, David G. T.
988 $a20131213
049 $aBOHA
906 $0OCLC