Statistical Inference and Application for Partially Linear Models

Jing Zhang; Hong Xia Guo

doi:10.4028/www.scientific.net/AMM.733.910

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 733Statistical Inference and Application for...

Statistical Inference and Application for Partially Linear Models

Abstract:

As partially linear regression model contains parameters part and the nonparametric part, it is better than the linear model. Partially linear regression model is more freedom, flexible, and can seize the characteristics of data. This passage first reduces the dimension of expenditure index data using principal component analysis. Then based on the dimension-reduced data, a partial linear model is established to forecast expenditure on army. The results show a great advantage over those by stepwise linear regression analysis.

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Periodical:

Applied Mechanics and Materials (Volume 733)

Pages:

910-913

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.733.910

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Online since:

February 2015

Authors:

Jing Zhang*, Hong Xia Guo

Keywords:

Partially Linear Model, Principal Component Analysis, Stepwise Linear Regression Analysis

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