摘要
主要讨论线性测量误差模型在约束情况下的检验问题.基于比较原假设与备择假设下模型拟合残差平方和的思想构造了一种新的检验统计量,该检验统计量在原假设下服从加权卡方分布.通过调整,得到了一个渐近零分布为标准卡方分布的检验统计量.最后,通过数值模拟验证了所提推断方法的有效性.
This paper considers are measured with additive error testing for linear regression and some additional linear model when covariates restrictions on the coefficients are available. We propose a test statistic based on the difference between the corrected residual sums of squares under the null and alterative hypotheses, and show that its limiting distribution is a weighted sum of independent chi-square distributions. We also develop an adjusted test statistic, which has an asymptotically standard chisquared distribution. Finally, some simulations are given to examine the performance of our procedure and the results are satisfactory.
出处
《系统科学与数学》
CSCD
北大核心
2013年第2期171-178,共8页
Journal of Systems Science and Mathematical Sciences
基金
中央高校基本科研业务费专项资金
中央民族大学自主科研项目(1112KYZYTS44)资助课题
关键词
线性回归模型
测量误差
校正最小二乘估计
约束估计
Linear regression models, measurement errors, corrected least squaresestimation, constrained estimation.