The spatial change features of relations between the precipitation on the one hand and longitude,latitude and the altitude above sea level on the other hand are analysed by means of geographically weighted regression and mixed geographically weighted regression.

This paper introduces the global stationary test of regression relation and the stationary test of each regression coefficient changes with spatial location in geographically weighted regression model by theory of least squares estimate.

Based on the data observatory from 216 weather stations in the main land of China from 1961 to 2000,the spatially-varying characteristics of the relationships between the annual precipitation and altitude are analyzed by the geographically weighted regression technique.

Two kinds of estimation of mixed geographically weighted regression model;

The spatial change features of relations between the precipitation on the one hand and longitude,latitude and the altitude above sea level on the other hand are analysed by means of geographically weighted regression and mixed geographically weighted regression.

Using geographical weighed regression(GWR) model of spatial varying-coefficient regression models(SVCRM) of spatial econometrics,this paper analyses the locally relationship between electricity consumption and economic development of 30 Chinese provinces.

With the kernel weight based on similarly between target gene and sample genes,which localize missing value estimation,a new method based on weighted regression is presented.

The weighted regression and nonlinear fitting model parameter optimization method are adopted to make regression analysis of observed data of landslide in different length of period.