DirichletDistribution (Built-in Mathematica Symbol)

DirichletDistribution[{\[Alpha]_1, ..., \[Alpha] k +1}] represents a Dirichlet distribution of dimension k with shape parameters \[Alpha]_i.

DiscreteUniformDistribution (Built-in Mathematica Symbol)

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

GompertzMakehamDistribution (Built-in Mathematica Symbol)

GompertzMakehamDistribution[\[Lambda], \[Xi]] represents a Gompertz distribution with scale parameter \[Lambda] and frailty parameter ...

LogitModelFit (Built-in Mathematica Symbol)

LogitModelFit[{y_1, y_2, ...}, {f_1, f_2, ...}, x] constructs a binomial logistic regression model of the form 1/(1 + E -(\[Beta]_0 + \[Beta]_1 f_1 + \[Beta]_2 f_2 + \ ...)) ...

LogLogPlot (Built-in Mathematica Symbol)

LogLogPlot[f, {x, x_min, x_max}] generates a log-log plot of f as function of x from x_min to x_max. LogLogPlot[{f_1, f_2, ...}, {x, x_min, x_max}] generates log-log plots of ...

LogNormalDistribution (Built-in Mathematica Symbol)

LogNormalDistribution[\[Mu], \[Sigma]] represents a lognormal distribution derived from a normal distribution with mean \[Mu] and standard deviation \[Sigma].

MaxStableDistribution (Built-in Mathematica Symbol)

MaxStableDistribution[\[Mu], \[Sigma], \[Xi]] represents a generalized maximum extreme value distribution with location parameter \[Mu], scale parameter \[Sigma], and shape ...

MinStableDistribution (Built-in Mathematica Symbol)

MinStableDistribution[\[Mu], \[Sigma], \[Xi]] represents a generalized minimum extreme value distribution with location parameter \[Mu], scale parameter \[Sigma], and shape ...

Moment (Built-in Mathematica Symbol)

Moment[list, r] gives the r\[Null]^th sample moment of the elements in list.Moment[dist, r] gives the r\[Null]^th moment of the symbolic distribution dist.Moment[..., {r_1, ...

MultinormalDistribution (Built-in Mathematica Symbol)

MultinormalDistribution[\[Mu], \[CapitalSigma]] represents a multivariate normal (Gaussian) distribution with mean vector \[Mu] and covariance matrix \[CapitalSigma].