Efficient Mean Estimation in Log-Normal Linear Models with First-Order Correlated Errors

Efficient Mean Estimation in Log-Normal Linear Models with First-Order Correlated Errors

Year:    2013

Author:    Song Zhang, Dehui Wang

Communications in Mathematical Research , Vol. 29 (2013), Iss. 3 : pp. 271–279

Abstract

In this paper, we propose a log-normal linear model whose errors are first-order correlated, and suggest a two-stage method for the efficient estimation of the conditional mean of the response variable at the original scale. We obtain two estimators which minimize the asymptotic mean squared error (MM) and the asymptotic bias (MB), respectively. Both the estimators are very easy to implement, and simulation studies show that they are perform better.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/2013-CMR-19010

Communications in Mathematical Research , Vol. 29 (2013), Iss. 3 : pp. 271–279

Published online:    2013-01

AMS Subject Headings:    Global Science Press

Copyright:    COPYRIGHT: © Global Science Press

Pages:    9

Keywords:    log-normal first-order correlated maximum likelihood two-stage estimation mean squared error.

Author Details

Song Zhang

Dehui Wang