MARC Record from marc_columbia

LEADER: 05699cam a2200661Ma 4500
001 15069677
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006 m o d
007 cr cnu||||||||
008 060828s2003 flua ob 000 0 eng d
035 $a(OCoLC)ocn123430098
035 $a(NNC)15069677
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020 $a1584883189
020 $a9781584883180
020 $a1420035266$q(electronic bk.)
020 $a9781420035261$q(electronic bk.)
024 7 $a10.1201/9781420035261$2doi
035 $a(OCoLC)123430098$z(OCoLC)71197442$z(OCoLC)150388306$z(OCoLC)276796528$z(OCoLC)647585395$z(OCoLC)779917866$z(OCoLC)992060738$z(OCoLC)994995536$z(OCoLC)1006806774$z(OCoLC)1031042036$z(OCoLC)1047530182$z(OCoLC)1058549001$z(OCoLC)1102535403
037 $aTANDF_184147$bIngram Content Group
050 4 $aQA279.5$b.R68 2003
060 4 $aQA279.5
072 7 $aMAT$x029010$2bisacsh
082 04 $a519.5/42$222
049 $aZCUA
100 1 $aRowe, Daniel B.
245 10 $aMultivariate Bayesian statistics :$bmodels for source separation and signal unmixing /$cDaniel B. Rowe.
260 $aBoca Raton :$bChapman & Hall/CRC,$c©2003.
300 $a1 online resource (xx, 329 pages) :$billustrations
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
347 $adata file
500 $aTitle from PDF title page (viewed January 29, 2007).
504 $aIncludes bibliographical references.
505 0 $aIntroduction; Part l: FUNDAMENTALS; STATISTICAL DISTRIBUTIONS; Scalar Distributions; Vector Distributions; Matrix Distributions; INTRODUCTORY BAYESIAN STATISTICS; Discrete Scalar Variables; Continuous Scalar Variables; Continuous Vector Variables; Continuous Matrix Variables; PRIOR DISTRIBUTIONS; Vague Priors; Conjugate Priors; Generaliz ed Priors; Correlation Priors; HYPERPARAMETER ASSESSMENT; Introduction; Binomial Likelihood; Scalar Normal Likelihood; Multivariate Normal Likelihood; Matrix Normal Likelihood; BAYESIAN ESTIMATION METHODS; Marginal Posterior Mean; Maximum a Posteriori; Advantages of ICM over Gibbs Sampling; Advantages of Gibbs Sampling over ICM; REGRESSION; Introduction; Normal Samples; Simple Linear Regression; Multiple Linear Regression; Multivariate Linear Regression; ; Part II: II Models; BAYESIAN REGRESSION; Introduction; The Bayesian Regression.
505 0 $aModel; Likelihood; Conjugate Priors and Posterior; Conjugate Estimation and Inference; Generalized Priors and Posterior; Generalized Estimation and Inference; Interpretation; Discussion; BAYESIAN FACTOR ANALYSIS; Introduction; The Bayesian Factor Analysis Model; Likelihood; Conjugate Priors and Posterior; Conjugate Estimation and Inference; Generalized Priors and Posterior; Generalized Estimation and Inference; Interpretation; Discussion; BAYESIAN SOURCE SEPARATION; Introduction; Source Separation Model; Source Separation Likelihood; Conjugate Priors and Posterior; Conjugate Estimation and Inference; Generalized Priors and Posterior; Generalized Estimation and Inference; Interpretation; Discussion; UNOBSERVABLE AND OBSERVABLE SOURCE SEPARATION; Introduction; Model; Likelihood; Conjugate Priors and Posterior; Conjugate Estimation and Inference; Generalized Priors and Posterior; Generalized Estimation and.
505 0 $aInference; Interpretation; Discussion; FMRI CASE STUDY; Introduction; Model; Priors and Posterior; Estimation and Inference; Simulated FMRI Experiment; Real FMRI Experiment; FMRI Conclusion; ; Part III: Generalizations; DELAYED SOURCES AND DYNAMIC COEFFICIENTS; Introduction; Model; Delayed Constant Mixing; Delayed Nonconstant Mixing; Instantaneous Nonconstant Mixing; Likelihood; Conjugate Priors and Posterior; Conjugate Estimation and Inference; Generalized Priors and Posterior; Generalized Estimation and Inference; Interpretation; Discussion; CORRELATED OBSERVATION AND SOURCE VECTORS; Introduction; Model; Likelihood; Conjugate Priors and Posterior; Conjugate Estimation and Inference; Posterior Conditionals; Generalized Priors and Posterior; Generalized Estimation and Inference; Interpretation; Discussion; CONCLUSION; Appendix A FMRI Activation Determination; Appendix B FMRI Hyperparameter.
650 0 $aBayesian statistical decision theory.
650 0 $aMultivariate analysis.
650 2 $aBayes Theorem
650 2 $aMultivariate Analysis
650 6 $aThéorie de la décision bayésienne.
650 6 $aAnalyse multivariée.
650 6 $aThéorème de Bayes.
650 7 $aMATHEMATICS$xProbability & Statistics$xBayesian Analysis.$2bisacsh
650 7 $aBayesian statistical decision theory.$2fast$0(OCoLC)fst00829019
650 7 $aMultivariate analysis.$2fast$0(OCoLC)fst01029105
650 17 $aMethode van Bayes.$2gtt
650 17 $aMultivariate analyse.$2gtt
655 0 $aElectronic books.
655 4 $aElectronic books.
776 08 $iPrint version:$aRowe, Daniel B.$tMultivariate Bayesian statistics.$dBoca Raton, Fla. : Chapman & Hall/CRC, ©2003$z1584883189$w(DLC) 2002031598$w(OCoLC)50582915
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio15069677$zTaylor & Francis eBooks
852 8 $blweb$hEBOOKS