2? Degrees
2α Degrees
A01=Broemeling
advanced Bayesian linear modeling techniques
Approximate Bayes Estimators
Approximate Densities
ARMA Class
ARMA Model
Author_Broemeling
Bayesian Predictive Density
Category=PB
Category=PDN
Conditional Posterior Distributions
Conjugate Class
Conjugate Prior Density
Distributed Lag Model
distribution
econometric applications
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eq_nobargain
eq_non-fiction
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HPD Interval
hypothesis testing methods
Joint Posterior Density
Location Vector
Lyle D. Broemeling
Marginal Posterior Density
Marginal Posterior Distribution
Marginal Prior Density
Minimum Norm Quadratic Unbiased Estimation
mixed effects models
multivariate analysis
Multivariate Linear Model
posterior
Posterior Density
Posterior Distribution
Posterior Mass Function
Precision Matrix
Predictive Density
Prior Density
Proper Prior Density
statistical inference
time series modeling
Product details
- ISBN 9780824785826
- Weight: 1600g
- Dimensions: 156 x 234mm
- Publication Date: 06 Dec 1984
- Publisher: Taylor & Francis Inc
- Publication City/Country: US
- Product Form: Hardback
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With Bayesian statistics rapidly becoming accepted as a way to solve applied statisticalproblems, the need for a comprehensive, up-to-date source on the latest advances in thisfield has arisen.Presenting the basic theory of a large variety of linear models from a Bayesian viewpoint,Bayesian Analysis of Linear Models fills this need. Plus, this definitive volume containssomething traditional-a review of Bayesian techniques and methods of estimation, hypothesis,testing, and forecasting as applied to the standard populations ... somethinginnovative-a new approach to mixed models and models not generally studied by statisticianssuch as linear dynamic systems and changing parameter models ... and somethingpractical-clear graphs, eary-to-understand examples, end-of-chapter problems, numerousreferences, and a distribution appendix.Comprehensible, unique, and in-depth, Bayesian Analysis of Linear Models is the definitivemonograph for statisticians, econometricians, and engineers. In addition, this text isideal for students in graduate-level courses such as linear models, econometrics, andBayesian inference.
Broemeling\,
