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 + \ ...)) ...

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 + \ ...

ListCorrelate (Built-in Mathematica Symbol)

ListCorrelate[ker, list] forms the correlation of the kernel ker with list. ListCorrelate[ker, list, k] forms the cyclic correlation in which the k \[Null]^th element of ker ...

MatrixForm (Built-in Mathematica Symbol)

MatrixForm[list] prints with the elements of list arranged in a regular array.

WaveletMapIndexed (Built-in Mathematica Symbol)

WaveletMapIndexed[f, wd] applies the function f to the arrays of coefficients and indices of a ContinuousWaveletData or DiscreteWaveletData object.WaveletMapIndexed[f, dwd, ...

Permutation Groups (Mathematica Tutorial)

Groups admit many different representations. In particular, all finite groups can be represented as permutation groups, that is, they are always isomorphic to a subgroup of ...

GeneralizedLinearModelFit (Built-in Mathematica Symbol)

GeneralizedLinearModelFit[{y_1, y_2, ...}, {f_1, f_2, ...}, x] constructs a generalized linear model of the form g -1 (\[Beta]_0 + \[Beta]_1 f_1 + \[Beta]_2 f_2 + ...) that ...

HistogramDistribution (Built-in Mathematica Symbol)

HistogramDistribution[{x_1, x_2, ...}] represents the probability distribution corresponding to a histogram of the data values x_i.HistogramDistribution[{{x_1, y_1, ...}, ...

NonlinearModelFit (Built-in Mathematica Symbol)

NonlinearModelFit[{y_1, y_2, ...}, form, {\[Beta]_1, ...}, x] constructs a nonlinear model with structure form that fits the y_i for successive x values 1, 2, ... using the ...

ProductDistribution (Built-in Mathematica Symbol)

ProductDistribution[dist_1, dist_2, ...] represents the joint distribution with independent component distributions dist_1, dist_2, ....