Conditional variance estimation in heteroscedastic regression models
Resource
Journal of Statistical Planning and Inference 139 (2): 236-245
Journal
Journal of Statistical Planning and Inference
Journal Volume
139
Journal Issue
2
Pages
236-245
Date Issued
2009
Author(s)
Abstract
First, we propose a new method for estimating the conditional variance in heteroscedasticity regression models. For heavy tailed innovations, this method is in general more efficient than either of the local linear and local likelihood estimators. Secondly, we apply a variance reduction technique to improve the inference for the conditional variance. The proposed methods are investigated through their asymptotic distributions and numerical performances. © 2008 Elsevier B.V. All rights reserved.
Type
journal article
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