A note on compatibility of conditional autoregressive models

Emanuela Dreassi and Pietro Rigo

Statistics & Probability Letters, 2017, vol. 125, issue C, 9-16

Abstract: Suppose that, to assess the joint distribution of a random vector (X1,…,Xn), one selects the kernels Q1,…,Qn with Qi to be regarded as a possible conditional distribution for Xi given (Xj:j≠i); Q1,…,Qn are compatible if there exists a joint distribution for (X1,…,Xn) with conditionals Q1,…,Qn. Similarly, Q1,…,Qn are improperly compatible if they can be obtained, according to the usual rule, with an improper distribution in place of a probability distribution. In this paper, compatibility and improper compatibility of Q1,…,Qn are characterized under some assumptions on their functional form. The characterization applies, in particular, if each Qi belongs to a one parameter exponential family. Special attention is paid to Gaussian conditional autoregressive models.

Keywords: Bayesian inference; CAR models; Compatibility of conditional distributions; Gibbs sampling; Improper distribution; Markov random fields (search for similar items in EconPapers)
Date: 2017
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DOI: 10.1016/j.spl.2017.01.008

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