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Non linear mapping (NLM) is a technique for obtaining a low-dimensional representation of the set of multivariate data, which operates by minimizing a function of the differences among the original inter-individual Euclidean distances and those in reduced dimensional space.
The function minimized is significantly a simple sum-of-squares.
Multilevel models are the regression models for the multilevel or clustered data where units i are nested in the clusters j, for example a cross-sectional study where students are
Chi-squared distribution : It is the probability distribution, f (x), of the random variable de?ned as the sum of squares of the number (v) of independent standard normal variables
Observational study is the study in which the objective is to discover cause-and-effect relationships but in which it is not feasible to use the controlled experimentation, in th
Machine learning is a term which literally means the ability of a machine to recognize patterns which have occurred repetitively and to improve its performance based on the past
Locally weighted regression is the method of regression analysis in which the polynomials of degree one (linear) or two (quadratic) are used to approximate regression function in
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
Unequal probability sampling is the sampling design in which the different sampling units in the population have different probabilities of being included in sample. The differing
O'Brien's two-sample tests are the extensions of the conventional tests for assessing the differences between treatment groups which take account of the possible heterogeneous nat
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
Non linear model : A model which is non-linear in the parameters, for instance are Some such type of models can be converted into the linear models by linearization (the s
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