Estimation of regression equation with cauchy disturbances
作者:
K.R. Kadiyala,
K.S.R. Murthy,
期刊:
Canadian Journal of Statistics
(WILEY Available online 1977)
卷期:
Volume 5,
issue 1
页码: 111-120
ISSN:0319-5724
年代: 1977
DOI:10.2307/3315088
出版商: Wiley‐Blackwell
关键词: Linear regression equation;Cauchy disturbances
数据来源: WILEY
摘要:
AbstractIn this paper we present two methods of estimating a linear regression equation with Cauchy disturbances. The first method uses the maximum likelihood principle and therefore the estimators obtained are consistent. The asymptotic covariance is derived which provides with the necessary statistics for the purpose of making inference in large samples. The second method is the method of least lines which minimizes the sum of absolute errors (MSAE) from the fitted regression. Then these two methods are compared through a Monte Carlo study. The maximum likelihood method emerges superior over theMSAEmethod. However, theMSAEprocedure which does not depend on the distribution of the error term appears to be a close competitor to the maximum likelihood estimator.
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