Expectation[expr, x \[Distributed] dist] gives the expectation of expr under the assumption that x follows the probability distribution dist. Expectation[expr, x ...

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 ...

This loads packages containing some test problems and utility functions. One of the first and simplest methods for solving initial value problems was proposed by Euler: ...

This package provides functions for the generation of standard waveforms and waveforms with user-specified spectra, the synthesis of amplitude and frequency modulated ...

Parallel kernels do not have access to the values of variables defined in the master kernel, nor do they have access to locally defined functions. Mathematica contains a ...

Widgets created within a user interface definition can be named and registered in an object registry for easy lookup reference by script code and other widgets. Complete ...

EmpiricalDistribution[{x_1, x_2, ...}] represents an empirical distribution based on the data values x_i.EmpiricalDistribution[{{x_1, y_1, ...}, {x_2, y_2, ...}, ...}] ...

ParallelTable[expr, {i_max}] generates in parallel a list of i_max copies of expr.ParallelTable[expr, {i, i_max}] generates in parallel a list of the values of expr when i ...

ReliefPlot[array] generates a relief plot of an array of height values.

SmoothDensityHistogram[{{x_1, y_1}, {x_2, y_2}, ...}] plots a smooth kernel histogram of the values {x_i, y_i}.SmoothDensityHistogram[{{x_1, y_1}, {x_2, y_2}, ...}, espec] ...