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Invariant transformations to combine marginal probability functions to form multivariate distributions motivated by the need to enlarge the class of multivariate distributions beyond the multivariate normal distribution and its related functions such as the multi- variate Student's t-distribution and the Wishart distribution. An example is Frank's family of bivariate distributions. (The word 'copula' comes from Latin and means to connect or join.) Quintessentially copulas are measures of the dependent structure of the marginal distributions and they have been used to model correlated risks, joint default probabilities in credit portfolios and groups of individuals that are exposed to similar economic and physical environments. Also used in frailty models for surveying.
Laplace distribution : The probability distribution, f(x), given by the following formula Can be derived as the distribution of the difference of two independent random var
Difference b/w historigram and histogram
Generally the final stage of an exploratory factor analysis in which factors derived initially are transformed to build their interpretation simpler. Generally the target of the pr
Probability judgements : Human beings often require assessing the probability which some event will occur and accuracy of these probability judgements often determines success of o
Canonical correlation analysis : A process of analysis for investigating the relationship between the two groups of variables, by ?nding the linear functions of one of the sets of
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Median absolute deviation (MAD) : It is the very robust estimator of the scale given by the following equation or, in other words we can say that, the median of the absolute
An approach to decrease the size of very large data sets in which the data are first 'binned' and then statistics such as the mean and variance/covariance are calculated on each bi
Mardia's multivariate normality test is a test that a set of the multivariate data arise from the multivariate normal distribution against departures due to the kurtosis. The test
Principal components regression analysis is a process often taken in use to overcome the problem of multicollinearity in the regression, when simply deleting a number of the expla
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