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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.
Window estimates is a term which occurs in the context of the both frequency domain and time domain estimation for the time series. In the previous it generally applies to weights
It is the technique used in the clinical trials when it is possible to make an acceptable place before an active treatment but not to make the two active treatments identical. In t
Conditional logistic regression : The form of logistic regression designed to work with the clustered data, such as data including matched pairs of the subjects, in which subject-s
Blinder Oaxaca method: A method or technique used for assessing the effect of the role of income on racial wealth gap. The method or technique is based on the decomposition of the
Length-biased data is a data which arise when the probability that an item is sampled is proportional to its own length. A main example of this situation occurs in the renewal the
Computer-aided diagnosis : The computer programs which are designed to support clinical decision making. In common, such systems are based on the repeated application of the Bay
Randomization tests are the procedures for determining the statistical significance directly from the data with- out recourse to some particular sampling distribution. For instanc
Relative risk is the measure of the association between the exposure to a particular factor and the risk or probability of a convinced outcome, calculated as follows therefor
Particlefilters is a simulation method for tracking moving target distributions and for reducing computational burden of the dynamic Bayesian analysis. The method uses a Markov ch
Prevalence : The measure of the number of people in a population who have a certain disease at a given point in time. It c an be measured by two methods, as point prevalence and p
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