Minimum-volume confidence sets of unknown parameters based on ridge estimator of linear models
This studys selects linear regression models with a normal distribution of errors and uses the relation between the least squares estimation and the ridge estimation of the additional pseudo-observational data model,to calculate the minimum volume confidence sets(intervals or regions)of unknown parameters based on ridge estimate.Compared with the classical confidence sets,the confidence sets gained on the basis of minimum volume is the best.Finally,it also gives some model examples,the results of which show that the confidence sets obtained in this study is more accurate and smaller in volume than the classical confidence sets.
万方数据
维普
