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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.
How large would the sample need to be if we are to pick a 95% confidence level sample: (i) From a population of 70; (ii) From a population of 450; (iii) From a population of 1000;
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
Prior distributions : The probability distributions which summarize the information about a random variable or parameter known or supposed at a given time instant, prior to attaini
Non-response is the term generally used for the failure to give the relevant information being collected in the survey. Poor response can be because of the variety of causes, for
Bioinformatics : Essentially the application of the information theory to biology to deal with the deluge of the information resulting from the advances in molecular biology. The m
Lexis diagram is the diagram for displaying the simultaneous effects of the two time scales (generally age and calendar time) on a rate. For instance, mortality rates from cancer
This is an alternative to the Newton-Raphson technique for optimization (finding out the minimum or the maximum) of some function, which includes replacing the matrix of second der
Formal graphical representation of the "causal diagrams" or the "path diagrams" where the relationships are directed but acyclic (that is no feedback relations allowed). Plays an
Quantile regression is an extension of the classical least squares from estimation of the conditional mean models to the estimation of the variety of models for many conditional q
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