On least absolute deviation estimators for one-dimensional chirp model
Ananya Lahiri, Debasis Kundu, Amit Mitra · Statistics · 2012
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.