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High-dimensional data: This term used for data sets which are characterized by the very large number of variables and a much more modest number of the observations. In the 21st century\ such data sets are collected in number of areas, such as, text/web data mining and bioinformatics. The job of extracting meaningful statistical and biological information from such data sets present many challenges for which a number of recent methodological developments, for instance, sure screening methods, lasso, and Dantzig selector, might be quite helpful.
Random allocation is a technique for creating the treatment and control groups particularly in accordance of the clinical trial. Subjects receive the active treatment or the place
An approach to investigations designed to recognize a particular medical condition in the large population, usually by means of a blood test, which might result in the considerable
Option-3 scheme is a scheme of measurement used in the situations investigating possible changes over the time in longitudinal data. The scheme is planned to prevent measurement o
Line-intersect sampling is a technique of unequal probability sampling for selecting the sampling units in the geographical area. A sample of lines is drawn in a study area and, w
Matching distribution is a probability distribution which arises in the following manner. Suppose that the set of n subjects, numbered 1; . . . ; n respectively, are arranged in
The graph for Partial Autocorrelation Function for RES1 shows that there is no autocorrelation even though there are alternating spikes because they fall inside the 5% significance
Reciprocal transformation is a transformation of the form y =1/x, which is specifically useful for certain types of variables. Resistances, for instance, become conductances, and
MAZ experiments : The Mixture-amount experiments which include control tests for which the entire amount of the mixture is set to zero. Examples comprise drugs (some patients do no
Population averaged models are the models for kind of clustered data in which the marginal expectation of response variable is the main focus of interest. An alternative approach
Perturbation theory : The theory useful in assessing how well a specific algorithm or the statistical model performs when the observations suffer less random changes. In very commo
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