Jackknife after bootstrap robust regression

الملخص EN

The least squares method has been in use in regression analysis mainly because of tradition and ease of computation, but this method may suffer a huge setback in the presence of unusual observation such as outliers and high leverage point.

In this paper our main objective was to use jackknife after bootstrap procedure in most of robust regression method like, M-estimator and MM-estimator.

Analytical examples are presented to show the effective of the deleted observation on the coefficients, and the behavior of jackknife after bootstrap in robust regression.