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Generalized principal components analysis: The non-linear version of the principal components analysis in which the goal is to determine the non-linear coordinate system which is most in agreement with the data configuration. For instance, for the bivariate data, y1,y2, if the quadratic coordinate system is sought, a variable z is defined as given below: with the coefficients being set up so that the variance of z is a maximum amongst all such quadratic functions of y1 and y2.
Censored observations : An observation xi on some variable of interest is consired to be censored if it is known that xi Li (left-censored)or xi Ui (right-censored) where Li and Ui
Latin square is an experimental design targeted at removing from the experimental error the variation from two extraneous sources so that a more sensitive test of the treatment ef
The non-trivial extraction of implicit, earlier unknown and potentially useful information from data, specifically high-dimensional data, using pattern recognition, artificial inte
PRINCIPLES OF MODELLING IN OR.
importance of mathamatical expection in business
Matching distribution is a probability distribution which arises in the following manner. Suppose that the set of n subjects, numbered 1; . . . ; n respectively, are arranged in
The method of summarizing the large amounts of data by forming the frequency distributions, scatter diagrams, histograms, etc., and calculating statistics like means variances and
Missing values : The observations missing from the set of data for some of the reason. In longitudinal studies, for instance, they might occur because subjects drop out of the stud
The GRE has a combined verbal and quantitative mean of 1000 and a standard deviation of 200.
Hazard regression is the procedure for modeling the hazard function which does not depend on the suppositions made in Cox's proportional hazards model, namely that the log-hazard
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