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 + \ ...
TransferFunctionModel[m, var] represents the model of the transfer-function matrix m with complex variable var.TransferFunctionModel[{num, den}, var] specifies the numerator ...
Mathematica provides built-in support for both programmatic and interactive image processing, fully integrated with Mathematica's powerful mathematical and algorithmic ...
Because GPUs are SIMD machines, to exploit CUDA's potential you must pose the problem in an SIMD manner. Computation that can be partitioned in such a way that each thread ...
The NumericalDifferentialEquationAnalysis package combines functionality for analyzing differential equations using Butcher trees, Gaussian quadrature, and Newton-Cotes ...
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[{x_1, x_2, ...}] represents the probability distribution corresponding to a histogram of the data values x_i.HistogramDistribution[{{x_1, y_1, ...}, ...
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 ...
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 ...
NSolve
(Built-in Mathematica Symbol) NSolve[expr, vars] attempts to find numerical approximations to the solutions of the system expr of equations or inequalities for the variables vars. NSolve[expr, vars, ...