[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.5351/CKSS.2009.16.2.383

Estimating Variance Function with Kernel Machine

Kim, Jong-Tae (Dept. of Statistics, Daegu Univ.)
Hwang, Chang-Ha (Dept. of Statistics, Dankook Univ.)
Park, Hye-Jung (Computer Course Div., Daegu Univ.)
Shim, Joo-Yong (Dept. of Applied Statistics, Catholic Univ. of Daegu)

Publication Information

Communications for Statistical Applications and Methods / v.16, no.2, 2009 , pp. 383-388 More about this Journal

Abstract

In this paper we propose a variance function estimation method based on kernel trick for replicated data or data consisted of sample variances. Newton-Raphson method is used to obtain associated parameter vector. Furthermore, the generalized approximate cross validation function is introduced to select the hyper-parameters which affect the performance of the proposed variance function estimation method. Experimental results are then presented which illustrate the performance of the proposed procedure.

Keywords

Heteroscedasticity; kernel trick; kernel function; hyper-parameters; generalized approximate cross validation function; variance function;

Citations & Related Records

Reference

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