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Calling .NET from Mathematica   (NETLink Tutorial)
.NET/Link provides Mathematica users with the ability to interact with arbitrary .NET types directly from Mathematica. You can create objects and call methods and properties ...
DirichletDistribution   (Built-in Mathematica Symbol)
DirichletDistribution[{\[Alpha]_1, ..., \[Alpha] k +1}] represents a Dirichlet distribution of dimension k with shape parameters \[Alpha]_i.
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 + \ ...)) ...
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 ...
PERTDistribution   (Built-in Mathematica Symbol)
PERTDistribution[{min, max}, c] represents a PERT distribution with range min to max and maximum at c.PERTDistribution[{min, max}, c, \[Lambda]] represents a modified PERT ...
ProbitModelFit   (Built-in Mathematica Symbol)
ProbitModelFit[{y_1, y_2, ...}, {f_1, f_2, ...}, x] constructs a binomial probit regression model of the form 1/2 (1 + erf((\[Beta]_0 + \[Beta]_1 f_1 + \[Beta]_2 f_2 + \ ...
RiceDistribution   (Built-in Mathematica Symbol)
RiceDistribution[\[Alpha], \[Beta]] represents a Rice distribution with shape parameters \[Alpha] and \[Beta].RiceDistribution[m, \[Alpha], \[Beta]] represents a ...
TransferFunctionModel   (Built-in Mathematica Symbol)
TransferFunctionModel[m, var] represents the model of the transfer-function matrix m with complex variable var.TransferFunctionModel[{num, den}, var] specifies the numerator ...
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