Article ID Journal Published Year Pages File Type
1152778 Statistics & Probability Letters 2014 8 Pages PDF
Abstract

Robust estimation procedures for linear and mixture linear errors-in-variables regression models are proposed based on the relationship between the least absolute deviation criterion and maximum likelihood estimation in a Laplace distribution. The finite sample performance of the proposed procedures is evaluated by simulation studies.

Related Topics
Physical Sciences and Engineering Mathematics Statistics and Probability
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