InverseChiSquareDistribution[\[Nu]] represents an inverse \[Chi]^2 distribution with \[Nu] degrees of freedom.InverseChiSquareDistribution[\[Nu], \[Xi]] represents a scaled ...

LogisticDistribution[\[Mu], \[Beta]] represents a logistic distribution with mean \[Mu] and scale parameter \[Beta].

LogLogisticDistribution[\[Gamma], \[Sigma]] represents a log-logistic distribution with shape parameter \[Gamma] and scale parameter \[Sigma].

SkewNormalDistribution[\[Mu], \[Sigma], \[Alpha]] represents a skew-normal distribution with shape parameter \[Alpha], location parameter \[Mu], and scale parameter \[Sigma].

SlideView[{expr_1, expr_2, ...}] represents an object in which the expr_i are set up to be displayed on successive slides. SlideView[{expr_1, expr_2, ...}, i] makes the ...

TriangularDistribution[{min, max}] represents a symmetric triangular statistical distribution giving values between min and max. TriangularDistribution[{min, max}, c] ...

TukeyLambdaDistribution[\[Lambda]] represents Tukey's lambda distribution with shape parameter \[Lambda].TukeyLambdaDistribution[\[Lambda], \[Mu], \[Sigma]] represents ...

This section is designed to discuss how to make compiled functions run efficiently. It will cover features that make them run faster, as well as problems that can make them ...

This tutorial discusses how to retrieve information about data types. When you create a table, you will need to refer to these data types. If you find that the examples in ...

ByteCount[expr] gives the number of bytes used internally by Mathematica to store expr.