DiscreteShift (Built-in Mathematica Symbol)

DiscreteShift[f, i] gives the discrete shift DiscreteShift[f(i), i] == f(i + 1). DiscreteShift[f, {i, n}] gives the multiple shift \[DiscreteShift]_i^n\ f.DiscreteShift[f, ...

DistributeDefinitions (Built-in Mathematica Symbol)

DistributeDefinitions[s_1, s_2, ...] distributes all definitions for the symbols s_i to all parallel kernels.DistributeDefinitions["context"] distributes definitions for all ...

FactorialMomentGeneratingFunction (Built-in Mathematica Symbol)

FactorialMomentGeneratingFunction[dist, t] gives the factorial moment generating function for the symbolic distribution dist as a function of the variable t. ...

FisherHypergeometricDistribution (Built-in Mathematica Symbol)

FisherHypergeometricDistribution[n, n_succ, n_tot, w] represents a Fisher noncentral hypergeometric distribution.

FisherZDistribution (Built-in Mathematica Symbol)

FisherZDistribution[n, m] represents a Fisher z distribution with n numerator and m denominator degrees of freedom.

HazardFunction (Built-in Mathematica Symbol)

HazardFunction[dist, x] gives the hazard function for the symbolic distribution dist evaluated at x.HazardFunction[dist, {x_1, x_2, ...}] gives the multivariate hazard ...

LevyDistribution (Built-in Mathematica Symbol)

LevyDistribution[\[Mu], \[Sigma]] represents a Lévy distribution with location parameter \[Mu] and dispersion parameter \[Sigma].

LyapunovSolve (Built-in Mathematica Symbol)

LyapunovSolve[a, c] finds a solution x of the matrix Lyapunov equation a.x + x.a\[ConjugateTranspose] == c.LyapunovSolve[a, b, c] solves a.x + x.b == c.LyapunovSolve[{a, d}, ...

MardiaCombinedTest (Built-in Mathematica Symbol)

MardiaCombinedTest[data] tests whether data follows a MultinormalDistribution using the Mardia combined test.MardiaCombinedTest[data, " property"] returns the value of " ...

MaxValue (Built-in Mathematica Symbol)

MaxValue[f, x] gives the maximum value of f with respect to x.MaxValue[f, {x, y, ...}] gives the maximum value of f with respect to x, y, .... MaxValue[{f, cons}, {x, y, ...