FinancialData["name"] gives the last known price or value for the financial entity specified by " name".FinancialData["name", start] gives a list of dates and daily closing ...

Huge numerical datasets are routine for Mathematica. Its powerful array primitives make large-scale array manipulation both easy to specify and highly efficient. And its ...

SkewNormalDistribution[\[Mu], \[Sigma], \[Alpha]] represents a skew-normal distribution with shape parameter \[Alpha], location parameter \[Mu], and scale parameter \[Sigma].

Cluster analysis is an unsupervised learning technique used for classification of data. Data elements are partitioned into groups called clusters that represent proximate ...

EmpiricalDistribution[{x_1, x_2, ...}] represents an empirical distribution based on the data values x_i.EmpiricalDistribution[{{x_1, y_1, ...}, {x_2, y_2, ...}, ...}] ...

Mathematica has over 3000 built-in functions and other objects, all based on a single unified framework, and all carefully designed to work together, both in simple ...

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

DiscreteUniformDistribution[{i_min, i_max}] represents a discrete uniform distribution over the integers from i_min to i_max.DiscreteUniformDistribution[{{i_min, i_max}, ...

PDF[dist, x] gives the probability density function for the symbolic distribution dist evaluated at x.PDF[dist, {x_1, x_2, ...}] gives the multivariate probability density ...

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