Robust and Partially Adaptive Estimation of Regression Models

Publisher Website
Google Scholar
Abstract
It is well known that least squares estimates can be very sensitive to departures from normality. Various robust estimators such as least absolute deviations (LAD), Lp estimators provide possible alternatives to least squares when such departures occur. This paper applies a partially adaptive technique to estimate the parameters of Sharpe's market model. This methodology is based on a generalized t-distribution and includes as special cases least squares, LAD, Lp as well as some estimation procedures which have bounded and redescending influence functions.

This publication has 0 references indexed in Scilit: