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 ...
WishartDistribution[\[CapitalSigma], m] represents a Wishart distribution with scale matrix \[CapitalSigma] and degrees of freedom parameter m.
FrechetDistribution[\[Alpha], \[Beta]] represents the Frechet distribution with shape parameter \[Alpha] and scale parameter \[Beta].FrechetDistribution[\[Alpha], \[Beta], ...
AndersonDarlingTest[data] tests whether data is normally distributed using the Anderson\[Dash]Darling test.AndersonDarlingTest[data, dist] tests whether data is distributed ...
MinStableDistribution[\[Mu], \[Sigma], \[Xi]] represents a generalized minimum extreme value distribution with location parameter \[Mu], scale parameter \[Sigma], and shape ...
CramerVonMisesTest[data] tests whether data is normally distributed using the Cramér\[Dash]von Mises test.CramerVonMisesTest[data, dist] tests whether data is distributed ...
Mathematica's unified symbolic architecture immediately allows it to perform structural transformations not only on objects like lists, but also on general symbolic ...
KolmogorovSmirnovTest[data] tests whether data is normally distributed using the Kolmogorov\[Dash]Smirnov test.KolmogorovSmirnovTest[data, dist] tests whether data is ...
Erf
(Built-in Mathematica Symbol) Erf[z] gives the error function erf(z). Erf[z_0, z_1] gives the generalized error function erf(z_1) - erf(z_0).
KuiperTest[data] tests whether data is normally distributed using the Kuiper test.KuiperTest[data, dist] tests whether data is distributed according to dist using the Kuiper ...