A Note on Robustness of Normal Variance Estimators Under t-Distributions
學年 93
學期 2
出版（發表）日期 2005-05-01
作品名稱 A Note on Robustness of Normal Variance Estimators Under t-Distributions
作品名稱（其他語言）
著者 林志娟; Lin, Jyh-jiuan; Pal, Nabendu
單位 淡江大學統計學系
出版者 Philadelphia: Taylor & Francis Inc.
著錄名稱、卷期、頁數 Communications in Statistics: Theory and Methods 34(5), pp.1117-1126
摘要 In many real life problems one assumes a normal model because the sample histogram looks unimodal, symmetric, and/or the standard tests like the Shapiro-Wilk test favor such a model. However, in reality, the assumption of normality may be misplaced since the normality tests often fail to detect departure from normality (especially for small sample sizes) when the data actually comes from slightly heavier tail symmetric unimodal distributions. For this reason it is important to see how the existing normal variance estimators perform when the actual distribution is a t-distribution with k degrees of freedom (d.f.) (t k -distribution). This note deals with the performance of standard normal variance estimators under the t k -distributions. It is shown that the relative ordering of the estimators is preserved for both the quadratic loss as well as the entropy loss irrespective of the d.f. and the sample size (provided the risks exist).
關鍵字 Risk functions; Scale equivariant estimators; Primary 62C15; Secondary 62H12
語言 en
ISSN 0361-0926
期刊性質 國外
收錄於 SCI SSCI EI
產學合作
通訊作者
審稿制度
國別 USA
公開徵稿
出版型式 紙本
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