论文检索

双平方稳健回归估计的置信区间AI 解读

This paper describes the results from a Monte Carlo study of robust regression confidence-interval estimation in the model y = a + bx + ε. Bisquare estimators were studied on samples of 11 and 21 with five design matrices. Four estimators of scale were used to form confidence intervals. Samples were generated from two distributions: normal and slash. For many design matrices, the four scale estimators give almost equally efficient confidence intervals but require different t…

长尾对称分布下置信区间的稳健性AI 解读

A variety of 95-percent confidence interval procedures have been examined in some detail using Monte Carlo techniques. These estimators were tried on simulated samples of sizes 10 and 20 from a spectrum of distributions ranging from the Gaussian to the long-tailed Cauchy. The robustness of an estimator is measured by both the closeness of its level to the 5-percent goal (robustness of validity) and its expected length as compared to its competitors (robustness of…