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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.
Time series : The values of a variable recorded, generally at a regular interval, over the long period of time. The observed movement and fluctuations of several such series are
Healthy worker effect : The occurrence whereby employed individuals tend to have lower mortality rates than those who are unemployed. The effect, which can pose the serious problem
Lagging indicators: The part of a collection of the economic time series designed to give information about the broad swings in measures of the aggregate economic activity known a
Homoscedasticity - Reasons for Screening Data Homoscedasticity is the assumption that the variability in scores for a continuous variable is roughly the same at all values of
Lagrange Multiplier (LM) test The Null Hypothesis - H0: There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1: There is heteroscedasticity i.e. β 1
Regression through the origin : In some of the situations a relationship between the two variables estimated by the regression analysis is expected to pass by the origin because th
The initial evaluation of the set of observations to see whether or not they appear to satisfy the hypotheses or assumptions of the methods to be used in their analysis. Techniques
You have probably noticed by now that some of the statements of necessary and sufficient conditions sound more natural than others. For example it seems more natural to express "We
Models for the analysis of the survival times, or the time to event, data in which it is expected that a fraction of the subjects will not experience the event of interest. In a cl
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
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