Large deviations for posterior distributions on the parameter of a multivariate $$\text{ AR}(p)$$ process

Claudio Macci () and Stefano Trapani ()

Annals of the Institute of Statistical Mathematics, 2013, vol. 65, issue 4, 703-719

Abstract: We prove the large deviation principle for the posterior distributions on the (unknown) parameter of a multivariate autoregressive process with i.i.d. Normal innovations. As a particular case, we recover a previous result for univariate first-order autoregressive processes. We also show that the rate function can be expressed in terms of the divergence between two spectral densities. Copyright The Institute of Statistical Mathematics, Tokyo 2013

Keywords: Large deviation principle; Spectral density; Divergence; Relative entropy (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1007/s10463-012-0389-2

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