Model Confidence Set Based on Kullback-Leibler Divergence Distance

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Abstract:

Consider the problem of estimating true density, h(.) based upon a random sample X1,…, Xn. In general, h(.)is approximated using an appropriate in some sense, see below) model fƟ(x). This article using Vuong's (1989) test along with a collection of k(> 2) non-nested models constructs a set of appropriate models, say model confidence set, for unknown model h(.).Application of such confidence set has been confirmed through a simulation study.

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Journal title

volume 9  issue 2

pages  179- 193

publication date 2013-03

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