On the use of genetic algorithm with elitism in robust and nonparametric multivariate analysis

Chakraborty, Biman ; Chaudhuri, Probal (2003) On the use of genetic algorithm with elitism in robust and nonparametric multivariate analysis Austrian Journal of Statistics, 32 (1-2). pp. 13-27. ISSN 1026-597X

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Official URL: http://www.statistik.tuwien.ac.at/oezstat/brno03/p...

Abstract

In this paper, we provide a general formulation for the problems that arise in the computation of many robust and nonparametric estimates in terms of a combinatorial optimization problem. There is virtually no hope for solving such optimization problems exactly for high dimensional data, and people usually resort to various approximate algorithms many of which are based on heuristic search strategies. However, for such algorithms it is not guaranteed that they will converge to the global optimum as the number of iterations increases, and there are always possibilities for such algorithms with elitism as a way to solve that general problem by probabilistic search method. We establish convergence of our algorithm to the global optimal solution and demonstrate the performance of this algorithm using some numerical examples.

Item Type:Article
Source:Copyright of this article belongs to Austrian Statistical Society.
Keywords:Combinatorial Optimization; Crossover; Fitness; Iterated Conditional Modes; Halfspace Depth; Markov Chains; MCD Estimator; Mutation; Transformation Retransformation
ID Code:74624
Deposited On:17 Dec 2011 10:29
Last Modified:17 Dec 2011 10:29

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