LaplaceTransform[expr, t, s] gives the Laplace transform of expr. LaplaceTransform[expr, {t_1, t_2, ...}, {s_1, s_2, ...}] gives the multidimensional Laplace transform of ...
ExponentialPowerDistribution[\[Kappa], \[Mu], \[Sigma]] represents an exponential power distribution with shape parameter \[Kappa], location parameter \[Mu], and scale ...
HalfNormalDistribution[\[Theta]] represents a half-normal distribution with scale inversely proportional to parameter \[Theta].
CentralMomentGeneratingFunction[dist, t] gives the central moment generating function for the symbolic distribution dist as a function of the variable t. ...
NumericFunction is an attribute that can be assigned to a symbol f to indicate that f[arg_1, arg_2, ...] should be considered a numeric quantity whenever all the arg_i are ...
LevyDistribution[\[Mu], \[Sigma]] represents a Lévy distribution with location parameter \[Mu] and dispersion parameter \[Sigma].
InverseLaplaceTransform[expr, s, t] gives the inverse Laplace transform of expr. InverseLaplaceTransform[expr, {s_1, s_2, ...}, {t_1, t_2, ...}] gives the multidimensional ...
Probability[pred, x \[Distributed] dist] gives the probability for an event that satisfies the predicate pred under the assumption that x follows the probability distribution ...
KernelMixtureDistribution[{x_1, x_2, ...}] represents a kernel mixture distribution based on the data values x_i.KernelMixtureDistribution[{{x_1, y_1, ...}, {x_2, y_2, ...}, ...
Expectation[expr, x \[Distributed] dist] gives the expectation of expr under the assumption that x follows the probability distribution dist. Expectation[expr, x ...