Estimating Variance Function with Kernel Machine Kim, Jong-Tae; Hwang, Chang-Ha; Park, Hye-Jung; Shim, Joo-Yong;
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.