The Application Of Partial Linear Model In Tax Analysis And Prediction

Partial linear regression model is one of the hot spots of statistics research in the recent decades.It was provided by Engel etc.when they studied that the weather influenced on power demand.Since the partial linear regression model contains both the parametric and the nonparametric regression,it shares their both advantages,and it is more flexible.Since the advent of partial linear regression model,it has caused the attention of many scholars,and has achieved plenty of research results.It widely used in fields such as economy,finance and biomedicine.This paper first introduces several common semi parametric regression models and the development history of partial linear regression model and the research status at home and abroad.Secondly,this paper introduces several estimation method of regression function in nonparametric regression model and the method of selecting parameters of the smooth.On this basis,introduces the most common partial linear regression model.And combined with the least square and nonparametric estimation to estimate the parameters and nonparametric components of the partial linear regression model.At the same time,the test method of the model is introduced.Finally,this paper applies the partial linear regression model to the tax analysis and forecasting of Liaoning province.Select the main economic indicators data from the China Statistical Yearbook,using principal component analysis method to reduce data dimension,then we fitting partial linear regression model based on reduced dimension.Using this model to forecast the tax revenue of Liaoning Province in 2013.The results were better than the ordinary linear regression analysis method.