On least absolute deviation estimators for one-dimensional chirp model

It is well known that the least absolute deviation (LAD) estimators are more robust than the least squares estimators particularly in presence of heavy tail errors. We consider the LAD estimators of the unknown parameters of one-dimensional chirp signal model under independent and identically distri...

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Published in:Statistics (Berlin, DDR) DDR), 2014-03, Vol.48 (2), p.405-420
Main Authors: Lahiri, Ananya, Kundu, Debasis, Mitra, Amit
Format: Article
Language:English
Subjects:
asymptotic distribution
Chirp signals
Computer simulation
Deviation
Economic models
Estimating techniques
Estimators
least absolute deviation estimators
Parameter estimation
Regression analysis
strong consistency
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description It is well known that the least absolute deviation (LAD) estimators are more robust than the least squares estimators particularly in presence of heavy tail errors. We consider the LAD estimators of the unknown parameters of one-dimensional chirp signal model under independent and identically distributed error structure. The proposed estimators are strongly consistent and it is observed that the asymptotic distribution of the LAD estimators are normally distributed. We perform some simulation studies to verify the asymptotic theory for small sample sizes and the performance are quite satisfactory.
doi_str_mv 10.1080/02331888.2012.719519
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subjects asymptotic distribution
Chirp signals
Computer simulation
Deviation
Economic models
Estimating techniques
Estimators
least absolute deviation estimators
Parameter estimation
Regression analysis
strong consistency
title On least absolute deviation estimators for one-dimensional chirp model
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