Robust regression methods, such as RANSAC, suffer from a sensitivity to the scale parameter used for generating the inlier-outlier dichotomy. Projection based M-estimators (pbM) offer a solution to this by reframing the regression problem in a projection pursuit framework. In this paper we modify the pbM formulation to obtain an improved pbM algorithm. Furthermore, the modified algorithm is easily generalized to handle heteroscedastic data . The superior performance of heteroscedastic pbM, as compared to simple pbM, is experimentally verified.


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    Title :

    Heteroscedastic Projection Based M-Estimators


    Contributors:
    Subbarao, R. (author) / Meer, P. (author)


    Publication date :

    2005-01-01


    Size :

    270854 byte





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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