๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Empirical likelihood confidence region for parameter in the errors-in-variables models

โœ Scribed by Hengjian Cui; Song Xi Chen

Publisher
Elsevier Science
Year
2003
Tongue
English
Weight
206 KB
Volume
84
Category
Article
ISSN
0047-259X

No coin nor oath required. For personal study only.

โœฆ Synopsis

This paper proposes a constrained empirical likelihood confidence region for a parameter b 0 in the linear errors-in-variables model:

; which is constructed by combining the score function corresponding to the squared orthogonal distance with a constrained region of b 0 : It is shown that the coverage error of the confidence region is of order n ร€1 ; and Bartlett corrections can reduce the coverage errors to n ร€2 : An empirical Bartlett correction is given for practical implementation. Simulations show that the proposed confidence region has satisfactory coverage not only for large samples, but also for small to medium samples.

๐Ÿ“œ SIMILAR VOLUMES

Likelihood Inference in the Errors-in-Va
Likelihood Inference in the Errors-in-Variables Model
โœ S.A. Murphy; A.W. Van Der Vaart ๐Ÿ“‚ Article ๐Ÿ“… 1996 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 987 KB

We consider estimation and confidence regions for the parameters : and ; based on the observations (X 1 , Y 1 ), ..., (X n , Y n ) in the errors-in-variables model X i = Z i +e i and Y i =:+;Z i + f i for normal errors e i and f i of which the covariance matrix is known up to a constant. We study th

On Parameter Estimation for Semi-linear
On Parameter Estimation for Semi-linear Errors-in-Variables Models
โœ Cui Hengjian; Li Rongcai ๐Ÿ“‚ Article ๐Ÿ“… 1998 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 425 KB

This paper studies a semi-linear errors-in-variables model of the form Y i = x$ i ;+ g(T i )+e i , X i =x i +u i (1 i n). The estimators of parameters ;, \_ 2 and of the smooth function g are derived by using the nearest neighbor-generalized least square method. Under some weak conditions, it is sho