Two-stage variational mode decomposition approach to enhance the estimates of variance function

被引：0

作者：

Dhanushya, S. ^{[1
]}

Palanisamy, T. ^{[1
]}

机构：

[1] Amrita Vishwa Vidyapeetham, Dept Math, Amrita Sch Engn, Coimbatore, Tamil Nadu, India

来源：

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION | 2023年 / 52卷 / 11期

关键词：

Heteroscedasticity; Difference-based initial estimates; Variational mode decomposition; Two-stage VMD; Smooth regression function; SQUARE SUCCESSIVE DIFFERENCE; REGRESSION; RATIO; VMD;

D O I：

10.1080/03610918.2021.1995750

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

A two-stage variational mode decomposition approach is explored in this article to estimate the variance function in a nonparametric heteroscedastic fixed design regression model. This estimate improves the results obtained by using variational mode decomposition in the case of smooth regression function. We noticed that the amount of improvement is depending on the smoothness of the variance function. Simulations and comparisons with the earlier methods are carried out to evaluate the performance of the proposed method.

引用

页码：5605 / 5614

页数：10

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