Support Vector Machine-based Modified Sp Statistic for Subset Selection with Non-Normal Error Terms

Q3 Mathematics

Journal of Modern Applied Statistical Methods Pub Date : 2020-05-15 DOI:10.22237/jmasm/1571545600

S. S. Desai, D. N. Kashid

引用次数: 1

Abstract

Support vector machine (SVM) is used for estimation of regression parameters to modify the sum of cross products (Sp). It works well for some nonnormal error distributions. The performance of existing robust methods and the modified Sp is evaluated through simulated and real data. The results show the performance of the modified Sp is good.

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基于支持向量机的改进Sp统计量的非正态误差项子集选择

利用支持向量机(SVM)对回归参数进行估计，修正向量积和(Sp)。它适用于一些非正态误差分布。通过仿真和实际数据对现有鲁棒方法和改进后的Sp的性能进行了评价。结果表明，改性后的Sp性能良好。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Modern Applied Statistical Methods STATISTICS & PROBABILITY-

CiteScore

0.50

自引率

0.00%

发文量

期刊介绍： The Journal of Modern Applied Statistical Methods is an independent, peer-reviewed, open access journal designed to provide an outlet for the scholarly works of applied nonparametric or parametric statisticians, data analysts, researchers, classical or modern psychometricians, and quantitative or qualitative methodologists/evaluators.