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Multi dimensional unfolding is the form of multidimensional scaling applicable to both the rectangular proximity matrices where the rows and columns refer to the different sets of stimuli, for instance, judges and soft drinks, and asymmetric proximity matrices, for instance, citations of journal A by journal B and vice versa. Unfolding was introduced as a manner of representing judges and stimuli on a single straight line so that the rank-order of the stimuli as determined by each of the judge is reflected by the rank order of the distance of stimuli to that judge.
Nearest-neighbour methods are the methods of discriminant analysis are based on studying the training set subjects much similar to the subject to be classified. Classification mig
Introduction to Generalized Linear Models (GLM) We introduce the notion of GLM as an extension of the traditional normal-theory-based linear regression models. This will be very
Group visible design is an arrangement of the v mn treatments in b blocks such that: * Each block comprises k distinct treatments k5v; * Each treatment is replicated r number
The model which arises in the context of estimating the size of the closed population where individuals within the population could be identified only during some of the observatio
Procrustes analysis is a technique of comparing the alternative geometrical representations of a group of multivariate data or of the proximity matrix, for instance, two competing
The computer programs designed to mimic the role of the expert human consultant. This type of systems are capable to cope with the complex problems of the medical decision makin
seven questions
The Expectation/Conditional Maximization Either algorithm which is the generalization of ECM algorithm attained by replacing some of the CM-steps of ECM which maximize the constrai
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
Recurrence risk : Usually the probability that an individual experiences an event of interest given previous experience(s) of the event; for example, the probability of recurrence
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