Extrapolation in parametric models with Laplace measurement error

For general parametric statistical models with some variables being contaminated with the Laplace measurement error, we propose an extrapolation algorithm to estimate the unknown parameters. By applying the conditional expectation directly to the target function, either the function to be optimized...

Full description

Saved in:
Bibliographic Details
Published inStat (International Statistical Institute) Vol. 11; no. 1
Main Authors Shi, Jianhong, Guo, Linruo, Bai, Xiuqin, Song, Weixing
Format Journal Article
LanguageEnglish
Published The Hague Wiley Subscription Services, Inc 01.12.2022
Subjects
Algorithms
Computer simulation
Error analysis
Extrapolation
Laplace distribution
measurement error
parametric regression
simulation
Statistical models
Online AccessGet full text

Cover

More Information
Summary:For general parametric statistical models with some variables being contaminated with the Laplace measurement error, we propose an extrapolation algorithm to estimate the unknown parameters. By applying the conditional expectation directly to the target function, either the function to be optimized or an estimation equation, the proposed algorithm successfully bypasses the simulation step in the classical simulation extrapolation procedure and thus provides a viable alternative to the classical simulation extrapolation algorithm. Large sample properties of the resulting estimator are discussed. Finite sample performance of the proposed extrapolation estimation procedure is demonstrated by examples and numerical simulation studies.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2049-1573
2049-1573
DOI:10.1002/sta4.500