NL repository
menu
검색
Library
Browse
Communities & Collections
By Date
Authors
Titles
Subject
My Repository
My Account
Receive email updates
Edit Profile
DSpace at EWHA
자연과학대학
통계학전공
Journal papers
View : 845 Download: 0
Semiparametric efficient estimators in heteroscedastic error models
Title
Semiparametric efficient estimators in heteroscedastic error models
Authors
Kim M.
;
Ma Y.
Ewha Authors
김미정
SCOPUS Author ID
김미정
Issue Date
2019
Journal Title
Annals of the Institute of Statistical Mathematics
ISSN
0020-3157
Citation
Annals of the Institute of Statistical Mathematics vol. 71, no. 1
Keywords
Heteroscedasticity
;
Semiparametric method
;
Standardized regression error
;
Variance function
Publisher
Springer Tokyo
Indexed
SCIE; SCOPUS
Document Type
Article
Abstract
In the mean regression context, this study considers several frequently encountered heteroscedastic error models where the regression mean and variance functions are specified up to certain parameters. An important point we note through a series of analyses is that different assumptions on standardized regression errors yield quite different efficiency bounds for the corresponding estimators. Consequently, all aspects of the assumptions need to be specifically taken into account in constructing their corresponding efficient estimators. This study clarifies the relation between the regression error assumptions and their, respectively, efficiency bounds under the general regression framework with heteroscedastic errors. Our simulation results support our findings; we carry out a real data analysis using the proposed methods where the Cobb–Douglas cost model is the regression mean. © 2017, The Institute of Statistical Mathematics, Tokyo.
DOI
10.1007/s10463-017-0622-0
Appears in Collections:
자연과학대학
>
통계학전공
>
Journal papers
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML
Show full item record
Find@EWHA
트윗하기
BROWSE
Communities & Collections
By Date
Authors
Titles
Subject