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Download COMPSTAT: Proceedings in Computational Statistics, 7th by E. B. Andersen (auth.), Dr. F. De Antoni, Professor N. PDF

By E. B. Andersen (auth.), Dr. F. De Antoni, Professor N. Lauro, Professor A. Rizzi (eds.)

When facing the layout or with the appliance of any technical procedure, which isn't very simple and trivial, one has to stand to the matter to figure out the allowable de­ viations of the approach features and the optimum vector of approach parameter tolerances. the necessity for the answer of this challenge is motivated with numerous severe fiscal and maite­ nance elements, among them the tendency to arrive the minimum construction price, the maximal procedure operation reliability are the main widespread. think that we're facing an process S, together with N parts represented through the procedure parame­ ters xi' i = 1, 2 . . . N, that are prepared in definite structu­ re so, that the ok, method capabilities F okay' okay = 1, 2 . . . IG , expres­ sing the thought of procedure houses, fullfil the F-FO~ AF, /1/ \'Ihere F = l F ok} Ie is the set of the particular procedure services, FO = lFOk}~ is the set of the nominal approach features and A F = l A F okay 1(;. } is the set zero f the a eleven zero w a b 1 e s emf y s t u n c ion t s de­ viations. The set F relies along with the process constitution additionally at the vector X = [Xi}N of the procedure parameters. think, that the approach constitution is invariant.

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Extra info for COMPSTAT: Proceedings in Computational Statistics, 7th Symposium held in Rome 1986

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Introduction The author of the present paper suggested two methods for categorical data problems that can mostly have exploratory applications. A version of the discriminant analysis procedure (Rudas, 1984) and a method for the reduction of dimensionality for categorical data problems (Rudas, 1985a). These procedures will be briefly outlined in Sections 1. and 2. The present paper is concerned with an algorithm to carry out the computations that, for both procedures require the finding of certain subsets of the variables with a maximum property.

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