CopulaDistribution[ker, {dist_1, dist_2, ...}] represents a copula distribution with kernel distribution ker and marginal distributions dist_1, dist_2, ....

NProbability[pred, x \[Distributed] dist] gives the numerical probability for an event that satisfies the predicate pred under the assumption that x follows the probability ...

By far the largest release since Version 1.0 in 1988, Version 6.0 added a remarkable breadth of new functionality. As well as introducing several major new fundamental ...

OrderDistribution[{dist, n}, k] represents the k\[Null]^th-order statistics distribution for n observations from the distribution dist.OrderDistribution[{dist, n}, {k_1, k_2, ...

The ability to generate pseudorandom numbers is important for simulating events, estimating probabilities and other quantities, making randomized assignments or selections, ...

HistogramList[{x_1, x_2, ...}] gives a list of bins and histogram heights of the values x_i.HistogramList[{{x_1, y_1, ...}, {x_2, y_2, ...}, ...}] gives a list of bins and ...

DistributionFitTest[data] tests whether data is normally distributed. DistributionFitTest[data, dist] tests whether data is distributed according to dist. ...

BoxWhiskerChart[{x_1, x_2, ...}] makes a box-and-whisker chart for the values x_i.BoxWhiskerChart[{x_1, x_2, ...}, bwspec] makes a chart with box-and-whisker symbol ...

Monte Carlo methods use randomly generated numbers or events to simulate random processes and estimate complicated results. For example, they are used to model financial ...

MomentEvaluate[mexpr, dist] evaluates formal moments in the moment expression mexpr on the distribution dist.MomentEvaluate[mexpr, list] evaluates formal moments and formal ...