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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.
Collective risk models : The models applied to insurance portfolios which do not create direct reference to the risk characteristics of individual members of the portfolio when des
What is statistical inference? Statistical inference can be defined as the method of drawing conclusions from data which are subject to random variations. This is based o
Barrett and Marshall Model for conception : A biologically reasonable model for the probability of conception in a particular menstrual cycle, which supposes that the batches of sp
Greenhouse geissercorrection is the method of adjusting the degrees of freedom of the within- subject F-tests in the analysis of the variance of longitudinal data so as to allow t
Categorical variable : A variable which provides the appropriate label of observation after the allocation to one of the several possible categories, for instance, the respiratory
Suppose that $4 million is available for investment in three projects. The probability distribution of the net present value earned from each project depends on how much is invest
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
Glim is the software package specifically suited for fitting the generalized linear models (the acronym stands for the Generalized Linear Interactive Modelling), including the log
Hypergeometric distribution is t he probability distribution related with the sampling without replacement from the population of finite size. If the population comprises of r ele
The distribution over distributions in the sense that each draw from the process is itself the distribution. The name Dirichlet process or procedure is due to the fact that the ?ni
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