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Discuss the use of dummy variables in both multiple linear regression and non-linear regression. Give examples if possible
Principal components analysis is a process for analysing multivariate data which transforms original variables into the new ones which are uncorrelated and account for decreasing
The Null Hypothesis - H0: γ 1 = γ 2 = ... = 0 i.e. there is no heteroscedasticity in the model The Alternative Hypothesis - H1: at least one of the γ i 's are not equal
Projection pursuit is a procedure for attaning a low-dimensional (usually two-dimensional) representation of the multivariate data, which will be particularly useful in revealing
Partial least squares is an alternative to the multiple regressions which, in spite of using the original q explanatory variables directly, constructs the new set of k regressor v
The values assigned to factors for the individual sample units in a factor analysis. The most common approach is "regression method". When the factors are seen as the random variab
Kalman filter : A recursive procedure which gives an estimate of the signal when only the 'noisy signal' can be observed. The estimate is efficiently constructed by putting the exp
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
Non-identified response is a term used to signify censored observations in survival data, which are not independent of the endpoint of the interest. Such observations can happen f
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
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