Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1152778 | Statistics & Probability Letters | 2014 | 8 Pages |
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
Authors
Jianhong Shi, Kun Chen, Weixing Song,