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 approach, which isn't very simple and trivial, one has to stand to the matter to figure out the allowable de viations of the process capabilities and the optimum vector of approach parameter tolerances. the necessity for the answer of this challenge is encouraged with quite a few severe monetary and maite nance features, among them the tendency to arrive the minimum creation expense, the maximal approach operation reliability are the main common. think that we're facing an method S, which include N parts represented via the process parame ters xi' i = 1, 2 . . . N, that are prepared in sure structu re so, that the ok, process services F okay' okay = 1, 2 . . . IG , expres sing the thought of procedure houses, fullfil the situation F-FO~ AF, /1/ \'Ihere F = l F ok} Ie is the set of the particular process services, FO = lFOk}~ is the set of the nominal procedure 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 in addition to the process constitution additionally at the vector X = [Xi}N of the process parameters. believe, that the method constitution is invariant.

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ESCOFIER, B. (1978), Analyse factorielle et distances repondant au principe d'equivalence distributionnelle, Rev. Stat. App. , XXVI, 4, 29-37. ESCOUFIER, Y. (1985), L' analyse des correspondances: ses proprietes et ses extensions. Bull. I. I. , Actes 45eme session, LI, 4, 28-3, 1-16. GREENACRE, M. J. (1984), Theory and applications of correspondence analysis, Academic Press, London. HAMOUDA, K. I. (1982),Repartition des crimes et delits au Koweit d'apres la nationalite des auteurs, Cah. An. Donn.

Before the strategy and the programs are presented it is however necessary to give a short review of the elements of the frame of reference of the complete analysis of which the initial screening is but only the first step. 1) The analysis discussed here will be performed within the framework of recursive log linear models. We presume, that is, that the set of response variables consists of several recursive or causal levels where the variables at a given level are to be taken as dependent on the variables at the lower levels as well as on the set of explanatory variable for the complete system of response variables.

Without entering into a long discussion, for which we refer to CAUSSINUS (1985b), we need to emphasize some points. 1. It is introduced to make clear the situations in which the statistical analysis will be consistent. And indeed when we display the rows of X on an Euclidean graphic, we assume implicitly that the points which are plotted represent the relevant part of the data while other dimensions contain only random noise It is then natural to suppose that this relevant part is a parameter Xi belonging to a subspace (or a linear manifold) whose dimension is the dimension of the graphical di splay, whi Ie the noi se is assumed to be a random error.

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