Distributions In Statistics Continuous Multivariate Distributions
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Distributions in Statistics: Continuous Multivariate Distributions
Systems of multivariate continuous distributions; Multinormal distributions; Bivariate and trivariate normal distributions; Multivariate t-distributions; Wishart distribution; Some other distributions associated with the multinormal distributions; Multivariate beta and gamma distributions; Multivariate extreme value and exponential distributions; Miscellaneous real multivariate distributions.
Continuous Multivariate Distributions
This authoritative treatment of continuous multivariate distributions (CMD) focuses on the many ways in which various statistical distributions have been constructed, investigated, and applied over the past thirty-plus years. With more than 300 updated references and additional software algorithms, this comprehensive Third Edition of what is widely recognized as the definitive work on statistical distributions, includes a unique collection that encompasses continuous multivariate distributions, discrete multivariate distributions, continuous univariate distributions, and univariate discrete distributions.
Continuous Multivariate Distributions, Volume 1
Continuous Multivariate Distributions, Volume 1, Second Edition provides a remarkably comprehensive, self-contained resource for this critical statistical area. It covers all significant advances that have occurred in the field over the past quarter century in the theory, methodology, inferential procedures, computational and simulational aspects, and applications of continuous multivariate distributions. In-depth coverage includes MV systems of distributions, MV normal, MV exponential, MV extreme value, MV beta, MV gamma, MV logistic, MV Liouville, and MV Pareto distributions, as well as MV natural exponential families, which have grown immensely since the 1970s. Each distribution is presented in its own chapter along with descriptions of real-world applications gleaned from the current literature on continuous multivariate distributions and their applications.