SechDistribution (Built-in Mathematica Symbol)

SechDistribution[\[Mu], \[Sigma]] represents the hyperbolic secant distribution with location parameter \[Mu] and scale parameter \[Sigma].

WakebyDistribution (Built-in Mathematica Symbol)

WakebyDistribution[\[Alpha], \[Beta], \[Gamma], \[Delta], \[Mu]] represents Wakeby distribution with shape parameters \[Beta] and \[Delta], scale parameters \[Alpha] and ...

Advice and Suggested Guidelines (Notation Package Tutorial)

The following are some issues and considerations to be aware of when using the Notation Package and/or designing notations. It is intrinsically difficult to debug something ...

\[EmptySet] (Mathematica Character Name)

Unicode: 2205. Alias: Esc es Esc. Letter-like form. Not the same as \[CapitalOSlash] or \[Diameter].

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 ...

StudentTDistribution (Built-in Mathematica Symbol)

StudentTDistribution[\[Nu]] represents a Student t distribution with \[Nu] degrees of freedom.StudentTDistribution[\[Mu], \[Sigma], \[Nu]] represents a Student t distribution ...

Numerical Solution of Partial ... (Mathematica Tutorial)

The numerical method of lines is a technique for solving partial differential equations by discretizing in all but one dimension, and then integrating the semi-discrete ...

NIntegrate Integration Strategies (Mathematica Tutorial)

An integration strategy is an algorithm that attempts to compute integral estimates that satisfy user-specified precision or accuracy goals. An integration strategy normally ...

Hierarchical Clustering Package (Hierarchical Clustering Package Tutorial)

The function FindClusters finds clusters in a dataset based on a distance or dissimilarity function. This package contains functions for generating cluster hierarchies and ...

Numerical Nonlinear Local Optimization (Mathematica Tutorial)

Numerical algorithms for constrained nonlinear optimization can be broadly categorized into gradient-based methods and direct search methods. Gradient search methods use ...