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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 <Title>Illustration of Bayesian Inference in Normal Data Models Using Gibbs Sampling</Title>

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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