In this paper,a new biased estimate,which is called the united regression estimate(URE),is proposed for the regression coefficient in multivariate linear models.

Furthermore,regression composite estimator is constructed by thes.

A comparative study of systematic sampling and regression estimate for controlling total volume was conducted.

Through combining the advantages of field theory with adaptive resonance theory and contraposing the characteristics of regression estimate problem, a novel neural network regression estimate algorithm FTART3 is proposed in this paper.

the principal component analysis and regression estimate.

The basic ideas of SVM for pattern recognition and regression are introduced.

A support vector machine for regression is presented.

Support Vector Machine (SVM) for regression has recently attracted growing research interest due to its obvious advantage such as nonlinear function approximation with arbitrary accuracy, and good generalization ability, unique and globally optimal solutions.

We give the approximation formulas of the variance of the sample regression estimator for a population mean and its saymptotically non-biased estimator in mult-stage sampling.

Some troubles emerge when we use regression estimator in such a case:in a continuous survey research,when the prior sample and the present sample are independent and they have different elements,we can not compute the regression coefficient.