Minimum distance conditional variance function checking in heteroscedastic regression models

Nishantha Samarakoon and Weixing Song

Journal of Multivariate Analysis, 2011, vol. 102, issue 3, 579-600

Abstract: This paper discusses a class of minimum distance tests for fitting a parametric variance function in heteroscedastic regression models. These tests are based on certain minimized L2 distances between a nonparametric variance function estimator and the parametric variance function estimator. The paper establishes the asymptotic normality of the proposed test statistics and that of the corresponding minimum distance estimator under the fitted model. These estimators turn out to be -consistent. Consistency of this sequence of tests at some fixed alternatives and asymptotic power under some local nonparametric alternatives are also discussed. Some simulation studies are conducted to assess the finite sample performance of the proposed test.

Keywords: Kernel; estimator; Lack-of-fit; test; Heteroscedasticity; Variance; function; L2; distance (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0047-259X(10)00233-2
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:102:y:2011:i:3:p:579-600

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

Access Statistics for this article

Journal of Multivariate Analysis is currently edited by de Leeuw, J.

More articles in Journal of Multivariate Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().