出版日期：2024-06-12 00:00:00

著者：Fan, Ya-yen; Tsai, Tzong-ru

著錄名稱、卷期、頁數：Mathematics 12(12),　1828

摘要：The bias of the maximum likelihood estimator can cause a considerable estimation error if the sample size is small. To reduce the bias of the maximum likelihood estimator under the small sample situation, the maximum likelihood and parametric bootstrap bias-correction methods are proposed in this study to obtain more reliable maximum likelihood estimators of the unit exponential distribution parameters. The procedure to implement the bias-corrected maximum likelihood estimation method is derived analytically, and the steps to obtain the bias-corrected bootstrap estimators are presented. The simulation results show that the proposed maximum likelihood bootstrap bias-correction method can significantly reduce the bias and mean squared error of the maximum likelihood estimators for most of the parameter combinations in the simulation study. A soil moisture data set and a numerical example are used for illustration.

關鍵字：bias;maximum likelihood estimation;moment;Newton–Raphson algorithm

語言：en_US

ISSN：2227-7390

期刊性質：國外

收錄於：SCI Scopus

審稿制度：是

國別：CHE

出版型式：電子版