A Non-iterative Bayesian Sampling Algorithm for Linear Regression Models with Scale Mixtures of Normal Distributions

The scale mixtures of Normal distributions are used as a robust alternative to the normal distribution in linear regression modelling, and a non-iterative Bayesian sampling algorithm is developed to obtain independently and identically distributed samples approximately from the observed posterior di...

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Veröffentlicht in:	Computational economics Jg. 49; H. 4; S. 579 - 597
Hauptverfasser:	Yang, Fengkai, Yuan, Haijing
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.04.2017 Springer Nature B.V
Schlagworte:	Algorithms Bayesian analysis Behavioral/Experimental Economics Computer Appl. in Social and Behavioral Sciences Convergence Economic theory Economic Theory/Quantitative Economics/Mathematical Methods Economics Economics and Finance Grammatical aspect Math Applications in Computer Science Measures Mixtures Normal distribution Operations Research/Decision Theory Prices Random variables Regression analysis Sampling Simulation Stock prices Students Studies Treasury bonds United States Inverse Bayesian formulae Gibbs sampling Model selection EM algorithm Scale mixtures of normal distributions
ISSN:	0927-7099, 1572-9974
Online-Zugang:	Volltext
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