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:: Volume 9, Issue 2 (3-2013) ::
JSRI 2013, 9(2): 179-193 Back to browse issues page
Model Confidence Set Based on Kullback-Leibler Divergence Distance
G. Barmalzan * , T. Payandeh Najafabad Amir
, ghbarmalzan@uoz.ac.ir
Abstract:   (2128 Views)

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.

Keywords: Kullback-Leibler divergence distance, confidence set, model selection, non-nested models, Vuong's test.
Full-Text [PDF 204 kb]   (619 Downloads)    
Type of Study: Research | Subject: General
Received: 2015/12/22 | Accepted: 2015/12/22 | Published: 2015/12/22
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Barmalzan G, Payandeh Najafabad T. Model Confidence Set Based on Kullback-Leibler Divergence Distance. JSRI. 2013; 9 (2) :179-193
URL: http://jsri.srtc.ac.ir/article-1-63-en.html


Volume 9, Issue 2 (3-2013) Back to browse issues page
مجله‌ی پژوهش‌های آماری ایران (علمی - پژوهشی) Journal of Statistical Research of Iran JSRI
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