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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.
The biggest and smallest variate values among the sample of observations. Significant in various regions, for instance flood levels of the river, speed of wind and snowfall.
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
The approach of controlling the error rate in an exploratory analysis where number of hypotheses are tested, but where the strict control which is provided by multiple comparison p
Profile plots is a technique of representing the multivariate data graphically. Each of the observation is represented by a diagram comprising of a sequence of equispaced vertical
Non parametric maximum likelihood (NPML) is a likelihood approach which does not need the specification of the full parametric family for the data. Usually, the non parametric max
Chain-binomial models : Models arising in mathematical theory of the quite infectious diseases, which postulate that at any stage in the epidemic there are a certain number of the
5. Packages from a machine a normally distributed with a mean 200g and its standard deviation 2grams. Find the probability that a package from the machine weighs a) Less than
Cohort component method : A broadly used method or technique of forecasting the age- and sex-speci?c population to the upcoming years, in which the initial population is strati?ed
L'Abbe ´ plot is often used in the meta-analysis of the clinical trials where the result is the binary response of it. The event risk (number of events/number of the patients in a
The model for data containing continuous and categorical variables both.The categorical data are summarized by the contingency table and their marginal distribution, 182by the mult
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