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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 + \ ...
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 ...
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 ...
LinearModelFit   (Built-in Mathematica Symbol)
LinearModelFit[{y_1, y_2, ...}, {f_1, f_2, ...}, x] constructs a linear model of the form \[Beta]_0 + \[Beta]_1 f_1 + \[Beta]_2 f_2 + ... that fits the y_i for successive x ...
Statistical Model Analysis   (Mathematica Tutorial)
When fitting models to data, it is often useful to analyze how well the model fits the data and how well the fitting meets the assumptions of the model. For a number of ...
Tensors   (Mathematica Tutorial)
Tensors are mathematical objects that give generalizations of vectors and matrices. In Mathematica, a tensor is represented as a set of lists, nested to a certain number of ...
Correlation   (Built-in Mathematica Symbol)
Correlation[v_1, v_2] gives the correlation between the vectors v_1 and v_2.Correlation[m] gives the correlation matrix for the matrix m.Correlation[m_1, m_2] gives the ...
FittedModel   (Built-in Mathematica Symbol)
FittedModel[...] represents the symbolic fitted model obtained from functions like LinearModelFit.
TotalVariation   (Multivariate Statistics Package Symbol)
TotalVariation[matrix] gives the total variation for matrix.
Descriptive Statistics   (Mathematica Guide)
Mathematica's descriptive statistics functions operate both on explicit data and on symbolic representations of statistical distributions. When operating on explicit data, ...
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