The extended skew Gaussian process for regression

被引：4

作者：

Alodat M.T. ^{[1
]}

Al-Rawwash M.Y. ^{[2
]}

机构：

[1] Department of Mathematics, Statistics and Physics, Qatar University, Doha

[2] Department of Mathematics, University of Sharjah, Sharjah

来源：

METRON | 2014年 / 72卷 / 3期

关键词：

Extended skew normal distribution; Gaussian process for regression;

D O I：

10.1007/s40300-014-0046-z

中图分类号：

学科分类号：

摘要：

In this article, we propose a generalization to the Gaussian process regression(GPR) model called the extended skew Gaussian process for regression (ESGP) model. The ESGP model works better than the GPR model when the errors are skewed. We derive the predictive distribution for the ESGP model at a new input. Also we apply the ESGP model to FOREX data and we find that it fits the Forex data better than the GPR model. © 2014 Sapienza Università di Roma.

引用

页码：317 / 330

页数：13

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