StableDistribution[type, \[Alpha], \[Beta], \[Mu], \[Sigma]] represents the stable distribution S_type with index of stability \[Alpha], skewness parameter \[Beta], location ...
MaxStableDistribution[\[Mu], \[Sigma], \[Xi]] represents a generalized maximum extreme value distribution with location parameter \[Mu], scale parameter \[Sigma], and shape ...
A variety of moments or combinations of moments are used to summarize a distribution or data. Mean is used to indicate a center location, variance and standard deviation are ...
Erfc
(Built-in Mathematica Symbol) Erfc[z] gives the complementary error function erfc(z).
FourierTransform[expr, t, \[Omega]] gives the symbolic Fourier transform of expr. FourierTransform[expr, {t_1, t_2, ...}, {\[Omega]_1, \[Omega]_2, ...}] gives the ...
DiscretePlot[expr, {n, n_max}] generates a plot of the values of expr when n runs from 1 to n_max.DiscretePlot[expr, {n, n_min, n_max}] generates a plot of the values of expr ...
PearsonDistribution[a_1, a_0, b_2, b_1, b_0] represents a distribution of the Pearson family with parameters a_1, a_0, b_2, b_1, and b_0.PearsonDistribution[type, a_1, a_0, ...
RiceDistribution[\[Alpha], \[Beta]] represents a Rice distribution with shape parameters \[Alpha] and \[Beta].RiceDistribution[m, \[Alpha], \[Beta]] represents a ...
WatsonUSquareTest[data] tests whether data is normally distributed using the Watson U^2 test.WatsonUSquareTest[data, dist] tests whether data is distributed according to dist ...
At the core of Mathematica is the foundational idea that everything —data, programs, formulas, graphics, documents—can be represented as symbolic expressions. And it is this ...