The combining generalized ridge and principal components estimator of regression coefficient in growth curve model;

The linear minimax estimation of regression coefficient in a general Gauss-Markov Model under balanced loss function

The relationship of the correlative coefficients and the regression coefficients is proved, and another new target P2 for the correlation degree among the described variables is put forward in the peper.

Admissible estimatiors for regression coefficients and parameters in multivariate stochastic effective linear model under restricted conditions;

Applying the principle of least square estimation and numerical solution of nonlinear equation, a new method is used to define regression coefficients in the pure nonlinear regression model that only one parameter appears in the nonlinear form.

This paper deals with the quantitative relations between regression coefficients and partial correlation coefficients in multivariate linear regression, and their statistical meanings.

Simultaneous detection of o-dihydroxybenzene、 m-dihydroxybenzene、p-dihydroxybenzenes by ridge regression;

Multi-factors Empirical analysis of health demands in china——Based on Ridge Regression;

The ridge regression method is applied to impedance inversion.

Simultaneous Determination of Iron and Platinum by Ridge Regression Atomic Absorption Spectrophotometry;

Simultaneous Determination of Lead and Palladium by Atomic Absorption Spectrophotometric and Ridge Regression;

Modified nonlinear ridge regression with optimal ridge parameter and its application to 4-CBA soft sensor;

Kernel ridge regression-based nonlinear internal model control

Improving the linear ridge regression by using the kernel function which meets the Mercer\'s condition,a novel nonlinear kernel ridge regression based on directly optimization was proposed.