Adrienne S. Glaich, MD; Leonard H. Goldberg, MD, FRCP; Tianhong Dai, PhD; Joy H. Kunishige, MD; Paul M. Friedman, MD; DermSurgery Associates, Houston, Texas (Drs Glaich, Goldberg, and Friedman); and Departments of Dermatology, Weill Cornell Medical College, Methodist Hospital, Houston (Drs Goldberg and Friedman), Harvard Medical School, Boston, Massachusetts (Dr Dai), and The University of Texa...

In this paper, we present a graphical method for selection of a good model among the several competitive models for the same data set. The proposed method not only selects the model but also tests the equal prediction accuracy of the models. The results of the proposed method are compared with that of the model selection using Friedman test.

The rapid expansion of the Internet has resulted not only in the ever-growing amount of data stored therein, but also in the burgeoning complexity of the concepts and phenomena pertaining to that data. This issue has been vividly compared by the renowned statistician J.F. Friedman (Friedman, 1997) of Stanford University to the advances in human mobility from the period of walking afoot to the e...

A COMBINED CHANNEL-MODIFIED ADAPTIVE ARRAY MMSE CANCELLER AND VITERBI EQUALIZER by Richard M Friedman In this thesis, a very simple scheme is proposed which couples a maximum-likelihood sequence estimator (MLSE) with a X-element canceller. The method makes use of the MLSE's channel estimator to modify the locally generated training sequence used to calculate the antenna array weights. This meth...

In this paper we present the theoretical background for destructive component identification in ensemble method via multivariate decompositions. The identification method is based on second order statistics and it is addressed for predictive models scored by MSE criterion. The validity of the concept is confirmed by simulation study based on Friedman benchmark function. Key-Words: Ensemble meth...