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1
Illustration of Bayesian Inference in Normal Data Models Us..:
Gelfand, Alan E.
;
Hills, Susan E.
;
Racine-Poon, Amy
.
Journal of the American Statistical Association. 85 (1990) 412 - p. 972-985 , 1990
Link:
https://www.jstor.org/stable/2289594
RT Journal T1
Illustration of Bayesian Inference in Normal Data Models Using Gibbs Sampling
UL https://suche.suub.uni-bremen.de/peid=jstor-2289594&Exemplar=1&LAN=DE A1 Gelfand, Alan E. A1 Hills, Susan E. A1 Racine-Poon, Amy A1 Adrian F. M. Smith PB American Statistical Association YR 1990 SN 0162-1459 K1 Marginalization K1 Variance components K1 Order-restricted inference K1 Hierarchical models K1 Missing data K1 Nonlinear parameters K1 Density estimation K1 Physical sciences K1 Physics K1 Mechanics K1 Density K1 Density measurement K1 Mathematics K1 Applied mathematics K1 Statistics K1 Applied statistics K1 Descriptive statistics K1 Statistical sampling K1 Sampling methods K1 Data sampling K1 Measures of variability K1 Statistical variance K1 Information science K1 Information management K1 Information classification K1 Cladistics K1 Bayesian inference K1 Data management K1 Data types K1 Behavioral sciences K1 Psychology K1 Cognitive psychology K1 Cognitive processes K1 Thought processes K1 Reasoning K1 Inference K1 Data products K1 Datasets K1 Statistical distributions K1 Normal distribution curve K1 Sampling distributions K1 Data architecture K1 Data models K1 Social sciences K1 Population studies K1 Population dynamics K1 Population growth K1 Population growth rate JF Journal of the American Statistical Association VO 85 IS 412 SP 972 OP 985 LK http://dx.doi.org/https://www.jstor.org/stable/2289594 DO https://www.jstor.org/stable/2289594 SF ELIB - SuUB Bremen
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