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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.
This is the branch of mathematics which deals with the theory of contests between two or more players under the specified sets of rules. The subject supposes a statistical aspect w
Observation-driven model is a term generally applied to models for the longitudinal data or time series which introduce within the unit correlation by specifying the conditional
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The procedure for clustering variables in the multivariate data, which forms the clusters by performing one or other of the below written three operations: * combining two varia
Harris and Stevens forecasting is the method of making short term forecasts in the time series which is subject to abrupt changes in pattern and the transient effects. Instances o
CONSTRUCTION OF AN OR MODEL
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A family of the probability distributions of the form given as here θ is the parameter and a, b, c, d are the known functions. It includes the gamma distribution, normal dis
Point scoring is an easy distribution free method which can be used for the prediction of a response which is a binary variable from the observations on several explanatory variab
The particular projection which an investigator believes is most likely to give an accurate prediction of the future value of some process. Commonly used in the context of the anal
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