OpenCLFunctionLoad (OpenCLLink Symbol)

OpenCLFunctionLoad[prog, fun, argtypes, blockdims] loads fun from source code prog, returning an OpenCLFunction object.OpenCLFunctionLoad[{progfile}, fun, argtypes, ...

Alphabetical Listing (Mathematica Guide)

Mathematica has over 3000 built-in functions and other objects, all based on a single unified framework, and all carefully designed to work together, both in simple ...

Moment (Built-in Mathematica Symbol)

Moment[list, r] gives the r\[Null]^th sample moment of the elements in list.Moment[dist, r] gives the r\[Null]^th moment of the symbolic distribution dist.Moment[..., {r_1, ...

PDF (Built-in Mathematica Symbol)

PDF[dist, x] gives the probability density function for the symbolic distribution dist evaluated at x.PDF[dist, {x_1, x_2, ...}] gives the multivariate probability density ...

Introduction to Graph Drawing (Mathematica Tutorial)

Mathematica provides functions for the aesthetic drawing of graphs. Algorithms implemented include spring embedding, spring-electrical embedding, high-dimensional embedding, ...

BubbleChart (Built-in Mathematica Symbol)

BubbleChart[{{x_1, y_1, z_1}, {x_2, y_2, z_2}, ...}] makes a bubble chart with bubbles at positions {x_i, y_i} with sizes z_i.BubbleChart[{..., w_i[{x_i, y_i, z_i}, ...], ...

Numerical Calculus Package (Numerical Calculus Package Tutorial)

The functions defined in the NumericalCalculus` context provide support for finding numerical solutions to calculus-related problems. This loads the package: The built-in ...

Parallelize (Built-in Mathematica Symbol)

Parallelize[expr] evaluates expr using automatic parallelization.

Numerical Nonlinear Global Optimization (Mathematica Tutorial)

Numerical algorithms for constrained nonlinear optimization can be broadly categorized into gradient-based methods and direct search methods. Gradient-based methods use first ...

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, ...}, ...