Some results for robust GM based estimators in heteroscedatic regression models

BIANCO, ANA; BOENTE, GRACIELA; DI RIENZO, JULIO

JOURNAL OF STATISTICAL PLANNING AND INFERENCE

Elsevier

Lugar: Amsterdam; Año: 2000 vol. 89 p. 215 - 242

0378-3758

In this paper the asymptotic behavior of robust estimates based on GM-estimators when the observations follow a regression model with random carriers and heteroscedastic errors is established. Also one-step Newton–Raphson and reweighted estimates for these models are introduced and their breakdown point is studied. Through a Monte Carlo study their performance for small samples is studied.