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 ...
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] ...
PairedBarChart[{y_1, y_2, ...}, {z_1, z_2, ...}] makes a paired bar chart with bar lengths y_1, y_2, ... and z_1, z_2, ..., respectively.PairedBarChart[{..., w_i[y_i, ...], ...
DiscretePlot[expr, {n, n_max}] generates a plot of the values of expr when n runs from 1 to n_max.DiscretePlot[expr, {n, n_min, n_max}] generates a plot of the values of expr ...
FinancialBond[params, ambientparams] gives the value of a financial bond instrument.FinancialBond[params, ambientparams, prop] computes the specified property prop.
The Mathematica compiler can run computations in parallel. It does this by threading a compiled function over lists of data in parallel. A first step is to create a compiled ...
ContourPlot[f, {x, x_min, x_max}, {y, y_min, y_max}] generates a contour plot of f as a function of x and y. ContourPlot[f == g, {x, x_min, x_max}, {y, y_min, y_max}] plots ...
This package contains descriptive statistics for multivariate data and distributions derived from the multivariate normal distribution. Distributions are represented in the ...
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 ...
BarChart3D[{y_1, y_2, ...}] makes a 3D bar chart with bar lengths y_1, y_2, ....BarChart3D[{..., w_i[y_i, ...], ..., w_j[y_j, ...], ...}] makes a 3D bar chart with bar ...