BAYESIAN LOGISTIC REGRESSION MODEL CHOICE VIA LAPLACE-METROPOLIS ALGORITHM

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ESKANDARI FARZAD; MESHKANI M.R.

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ISSN: 2588-4824

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Paper Information

Journal: JOURNAL OF THE IRANIAN STATISTICAL SOCIETY (JIRSS) Year:2006 | Volume:5 | Issue:1-2 Page(s): 9-24

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Information Journal Paper

Title

BAYESIAN LOGISTIC REGRESSION MODEL CHOICE VIA LAPLACE-METROPOLIS ALGORITHM

Author(s)

ESKANDARI FARZAD | MESHKANI M.R. | Issue Writer Certificate

Keywords

BAYES

BAYESIAN MODEL SELECTION

LAPLACE-METROPOLIS ALGORITHM

LOGISTIC REGRESSION

MULTINOMIAL DISTRIBUTION

Abstract

Following a BAYESian statistical inference paradigm, we provide an alternative methodology for analyzing a multivariate LOGISTIC REGRESSION. We use a multivariate normal prior in the BAYESian analysis. We present a unique BAYES estimator associated with a prior which is admissible. The BAYES estimators of the coefficients of the model are obtained via MCMC methods. The proposed procedure is illustrated by analyzing a data set which has previously been analyzed by various authors. It is shown that our model is more precise and computationally less taxing.

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APA: Copy

ESKANDARI, FARZAD, & MESHKANI, M.R.. (2006). BAYESIAN LOGISTIC REGRESSION MODEL CHOICE VIA LAPLACE-METROPOLIS ALGORITHM. JOURNAL OF THE IRANIAN STATISTICAL SOCIETY (JIRSS), 5(1-2), 9-24. SID. https://sid.ir/paper/555156/en

Vancouver: Copy

ESKANDARI FARZAD, MESHKANI M.R.. BAYESIAN LOGISTIC REGRESSION MODEL CHOICE VIA LAPLACE-METROPOLIS ALGORITHM. JOURNAL OF THE IRANIAN STATISTICAL SOCIETY (JIRSS)[Internet]. 2006;5(1-2):9-24. Available from: https://sid.ir/paper/555156/en

IEEE: Copy

FARZAD ESKANDARI, and M.R. MESHKANI, “BAYESIAN LOGISTIC REGRESSION MODEL CHOICE VIA LAPLACE-METROPOLIS ALGORITHM,” JOURNAL OF THE IRANIAN STATISTICAL SOCIETY (JIRSS), vol. 5, no. 1-2, pp. 9–24, 2006, [Online]. Available: https://sid.ir/paper/555156/en

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