Statistical Diagnosis And Countermeasure Based On Simulating A Kind Of Complicated Observation Data

In many areas of scientific research and actual production, there exists much work about analyzing and processing data. Analyzing and processing complicated observation data is very valuable and significant to actual application. In this paper, according to a kind of concrete complicated water and sediment observation data, we has carried on the statistical diagnosis to the complicated data which studied, established the multi- linear regression model and examined the model, at the same time we diagnosis this model based on the predecessor research work .Because there is a serious problem of the multi-correlations between independent variables, the ordinary least squares method has the possibility to cause the model unstable to prediction .Considered the sample capacity of the data is small, moreover the data has the multi-correlations, the model of partial least squares regression is established, using the method of partial least squares regression, meanwhile, considered the ridge regression can effectively eliminate the multi-correlations, the model of ridge regression is also established . Comparing the two kind of new regression models to the ordinary least squares model ,the result show that the method of partial least squares regression and ridge regression can reduce the mean square of parameters estimation, strengthen model generality and make the simulation effect to be better.This article luminescent spot is that the methods of partial least squares regression and ridge regression can improve the model ,then the precision of these regression models is compared according to the diagnosis of a kind of complicated observation data and in view of the question characteristic . Two kind of new regression models increase the generality of the model, and the model is stabler, the simulation effect surpasses the ordinary least squares method.