MultivariatePoissonDistribution (Built-in Mathematica Symbol)

MultivariatePoissonDistribution[\[Mu]_0, {\[Mu]_1, \[Mu]_2, \ ...}] represents a multivariate Poisson distribution with mean vector {\[Mu]_0 + \[Mu]_1, \[Mu]_0 + \[Mu]_2, ...

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, ...}, ...

ListStreamDensityPlot (Built-in Mathematica Symbol)

ListStreamDensityPlot[array] generates a stream density plot from a 2D array of vector and scalar field values {{vx_ij, vy_ij}, s_ij}. ListStreamDensityPlot[{{{x_1, y_1}, ...

ListVectorDensityPlot (Built-in Mathematica Symbol)

ListVectorDensityPlot[array] generates a vector plot from a 2D array of vector and scalar field values {{vx_ij, vy_ij}, s_ij}. ListVectorDensityPlot[{{{x_1, y_1}, {{vx_1, ...

MatrixExp (Built-in Mathematica Symbol)

MatrixExp[m] gives the matrix exponential of m. MatrixExp[m, v] gives the matrix exponential of m applied to the vector v.

LogNormalDistribution (Built-in Mathematica Symbol)

LogNormalDistribution[\[Mu], \[Sigma]] represents a lognormal distribution derived from a normal distribution with mean \[Mu] and standard deviation \[Sigma].

VectorPlot3D (Built-in Mathematica Symbol)

VectorPlot3D[{v_x, v_y, v_z}, {x, x_min, x_max}, {y, y_min, y_max}, {z, z_min, z_max}] generates a 3D vector plot of the vector field {v_x, v_y, v_z} as a function of x, y, ...

Formatting (SymbolicC Tutorial)

SymbolicC provides automated formatting of the generated C output. This section reviews some of the ways that you can work with formatting to create your own styles of ...

ListContourPlot (Built-in Mathematica Symbol)

ListContourPlot[array] generates a contour plot from an array of height values. ListContourPlot[{{x_1, y_1, f_1}, {x_2, y_2, f_2}, ...}] generates a contour plot from values ...

Introduction (Compiled Function Tools Tutorial)

The Mathematica compiler provides an important way both to speed up and also to work with Mathematica computations. It does this by taking assumptions about the computations ...