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Hill-climbing algorithm is an algorithm which is made in use in those techniques of cluster analysis which seek to find the partition of n individuals into g clusters by optimizing some numerical index of the clustering. Since it is not possible to consider every partition of n individuals into g groups (because of the enormous number of the partitions), the algorithm starts with some given initial partition and considers individuals in turn for moving into the other clusters, creating the move if it causes an improvement in the value of the clustering index. The procedure is continued until no move of the single individual causes an improvement.
The model which is applicable to the longitudinal data in which the dropout process might give rise to the informative lost values. Specifically if the study protocol specifies the
Battery reduction : A common term for reducing the number of variables of the interest in a study for the purposes of study and perhaps later data collection. For instance, an over
Regression diagnostics is the process designed to investigate the suppositions underlying particular forms of regression examination, for instance, homogeneity of variance, norma
Artificial neural network : A mathematical arrangement modelled on the human neural network and designed to attack various statistical problems, particularly in the region of patte
Computer-assisted interviews : A method or technique of interviewing subjects in which the interviewer reads the question from the computer screen instead of the printed page, and
Individual differences scaling is a form of multidimensional scaling applicable to the data comprising of a number of proximity matrices from the different sources that is differe
Model is the description of the supposed structure of a set of observations which can range from a fairly imprecise verbal account to, more commonly, a formalized mathematical exp
Longitudinal data : The data arising when each of the number of subjects or patients give rise to the vector of measurements representing same variable observed at the number of di
The nonparametric Bayesian inference approach to using the finite mixture distributions for modelling data suspected of the containing distinct groups of observations; this approac
Glejser test is the test for the heteroscedasticity in the error terms of the regression analysis which involves regressing the absolute values of the regression residuals for the
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