Development on statistical inference for matrix-valued statistics

2017 Fiscal Year Final Research Report

• Project/Area Number: 25330043
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Statistical science
• Research Institution: Japan Women's University
• Principal Investigator: Yoshihiko Konno 日本女子大学, 理学部, 教授 (00205577)
• Research Collaborator: EMURA Takeshi
• Project Period (FY): 2013-04-01 – 2018-03-31
• Keywords: ウィシャート分布 / 行列値統計量 / 統計的決定理論 / 最尤推定量 / 両側切断データ

Outline of Final Research Achievements

(1) Doubly truncated data consist of samples whose observed values fall between the right- and left- truncation limits. With such samples, the distribution function of interest is estimated using the nonparametric maximum likelihood estimator (NPMLE) that is obtained through a self-consistency algorithm.
(2) Biased sampling affects the inference for population parameters of interest if the sampling mechanism is not appropriately handled. This paper considers doubly-truncated data arising in lifetime data analysis in which samples are subject to both left- and right-truncations. To correct for the sampling bias with doubly-truncated data, maximum likelihood estimator (MLE) has been proposed under a parametric family called the special exponential family (Efron and Petrosian, in J Am Stat Assoc, 1999).

Free Research Field

数理統計学、多変量解析