SmoothHistogram[{x_1, x_2, ...}] plots a smooth kernel histogram of the values x_i.SmoothHistogram[{x_1, x_2, ...}, espec] plots a smooth kernel histogram with estimator ...
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, ...
WaveletScalogram[wd] plots wavelet vector coefficients in a DiscreteWaveletData or ContinuousWaveletData object wd.WaveletScalogram[wd, wind] plots wavelet coefficients ...
Exact global optimization problems can be solved exactly using Minimize and Maximize. This computes the radius of the circle, centered at the origin, circumscribed about the ...
A real polynomial system is an expression constructed with polynomial equations and inequalities combined using logical connectives and quantifiers and
Mathematica has a collection of commands that do unconstrained optimization (FindMinimum and FindMaximum) and solve nonlinear equations (FindRoot) and nonlinear fitting ...
All the test problems presented in [MGH81] have been coded into Mathematica in the Optimization`UnconstrainedProblems` package. A data structure is used so that the problems ...
BoxWhiskerChart[{x_1, x_2, ...}] makes a box-and-whisker chart for the values x_i.BoxWhiskerChart[{x_1, x_2, ...}, bwspec] makes a chart with box-and-whisker symbol ...
DistributionChart[{data_1, data_2, ...}] makes a distribution chart with a distribution symbol for each data_i.DistributionChart[{..., w_i[data_i, ...], ..., w_j[data_j, ...
The function FindClusters finds clusters in a dataset based on a distance or dissimilarity function. This package contains functions for generating cluster hierarchies and ...