Creating Palettes (Mathematica Tutorial)

Palettes are like extensions of your keyboard. They can be used to perform many actions in Mathematica, including entering typesetting characters, styling notebooks, and ...

Newton's Method (Mathematica Tutorial)

One significant advantage Mathematica provides is that it can symbolically compute derivatives. This means that when you specify Method->"Newton" and the function is ...

KernelMixtureDistribution (Built-in Mathematica Symbol)

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, ...}, ...

BenfordDistribution (Built-in Mathematica Symbol)

BenfordDistribution[b] represents a Benford distribution with base parameter b.

WalleniusHypergeometricDistribution (Built-in Mathematica Symbol)

WalleniusHypergeometricDistribution[n, n_succ, n_tot, w] represents a Wallenius noncentral hypergeometric distribution.

BetaDistribution (Built-in Mathematica Symbol)

BetaDistribution[\[Alpha], \[Beta]] represents a continuous beta distribution with shape parameters \[Alpha] and \[Beta].

InterpolatingPolynomial (Built-in Mathematica Symbol)

InterpolatingPolynomial[{f_1, f_2, ...}, x] constructs an interpolating polynomial in x which reproduces the function values f_i at successive integer values 1, 2, ... of x. ...

SkewNormalDistribution (Built-in Mathematica Symbol)

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

BenktanderWeibullDistribution (Built-in Mathematica Symbol)

BenktanderWeibullDistribution[a, b] represents a Benktander distribution of type II with parameters a and b.

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 + \ ...)) ...