Formatted Output (Mathematica Tutorial)

Ever since Version 3 of Mathematica, there has been rich support for arbitrary mathematical typesetting and layout. Underlying all that power was a so-called box language, ...

ListConvolve (Built-in Mathematica Symbol)

ListConvolve[ker, list] forms the convolution of the kernel ker with list. ListConvolve[ker, list, k] forms the cyclic convolution in which the k\[Null]^th element of ker is ...

MarginalDistribution (Built-in Mathematica Symbol)

MarginalDistribution[dist, k] represents a univariate marginal distribution of the k\[Null]^th coordinate from the multivariate distribution dist.MarginalDistribution[dist, ...

Plot3D (Built-in Mathematica Symbol)

Plot3D[f, {x, x_min, x_max}, {y, y_min, y_max}] generates a three-dimensional plot of f as a function of x and y. Plot3D[{f_1, f_2, ...}, {x, x_min, x_max}, {y, y_min, ...

TTest (Built-in Mathematica Symbol)

TTest[data] tests whether the mean of data is zero. TTest[{data_1, data_2}] tests whether the means of data_1 and data_2 are equal.TTest[dspec, \[Mu]_0] tests the mean ...

WaveletBestBasis (Built-in Mathematica Symbol)

WaveletBestBasis[dwd] computes a best basis representation in the DiscreteWaveletData object dwd.WaveletBestBasis[dwd, cspec] computes a best basis representation using the ...

DiscreteMath`GraphPlot` (Mathematica Compatibility Information)

GraphPlot functionality is now available in the newly added built-in Mathematica kernel functions GraphPlot and LayeredGraphPlot. GraphPlot3D is now available as the newly ...

ReverseBiorthogonalSplineWavelet (Built-in Mathematica Symbol)

ReverseBiorthogonalSplineWavelet[] represents a reverse biorthogonal spline wavelet of order 4 and dual order 2.ReverseBiorthogonalSplineWavelet[n, m] represents a reverse ...

RootLocusPlot (Built-in Mathematica Symbol)

RootLocusPlot[g, {k, k_min, k_max}] generates the root locus plot of a rational function g of k ranging from k_min to k_max.RootLocusPlot[sys, ...] plots the root loci of a ...

Random Number Generation (Mathematica Tutorial)

The ability to generate pseudorandom numbers is important for simulating events, estimating probabilities and other quantities, making randomized assignments or selections, ...