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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.
Homoscedasticity - Reasons for Screening Data Homoscedasticity is the assumption that the variability in scores for a continuous variable is roughly the same at all values of
A term commonly encountered in the analysis of the contingency tables. Such type of frequencies are the estimates of the values to be expected under hypothesis of interest. In a tw
an oil company is considering whether or not to bid for an offshore drilling contract. The bid would cost $60 with a 65% chance of gaining the contract. Outcome success Probability
Cauchy distribution : The probability distribution, f (x), can be given as follows where α is the position of the parameter (median) and the beta β a scale parameter. Moments
Quality-adjusted survival analysis is a method for evaluating the effects of treatment on survival which allows the consideration of quality of life as well as the quantity of lif
Ordination is the procedure of reducing the dimensionality (that is the number of variables) of multivariate data by deriving the small number of new variables which contain much
The variables appearing on the right-hand side of equations defining, for instance, multiple regressions or the logistic regression, and which seek to predict or 'explain' response
A value related with the square matrix which represents sums and products of its elements. For instance, if the matrix is then the determinant of A (conventionally written as
The distribution free or technique which is the analogue of the analysis of variance for the design with two factors. It can be applied to data sets which do not meet the assumptio
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 21 st
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