Database Connections (DatabaseLink Tutorial)

The first step in using a database is making a connection. This part of the tutorial discusses how to do this. If you are just starting to use DatabaseLink, you might want to ...

Introduction to J/Link (JLink Tutorial)

Welcome to J/Link, a product that integrates Mathematica and Java. J/Link lets you call Java from Mathematica in a completely transparent way, and it also lets you use and ...

Reference (CUDALink Tutorial)

CUDALink allows Mathematica to use the CUDA parallel computing architecture on Graphical Processing Units (GPUs). It contains functions that use CUDA-enabled GPUs to boost ...

Graph (Built-in Mathematica Symbol)

Graph[{e_1, e_2, ...}] yields a graph with edges e_j.Graph[{v 1, v 2, ...}, {e_1, e_2, ...}] yields the graph with vertices v_i and edges e_j. Graph[{..., w_i[v_i, ...], ...

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, ...

ListPlot3D (Built-in Mathematica Symbol)

ListPlot3D[array] generates a three-dimensional plot of a surface representing an array of height values. ListPlot3D[{{x_1, y_1, z_1}, {x_2, y_2, z_2}, ...}] generates a plot ...

PairedBarChart (Built-in Mathematica Symbol)

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, ...], ...

Termination Conditions (Mathematica Tutorial)

Mathematically, sufficient conditions for a local minimum of a smooth function are quite straightforward: x^* is a local minimum if ∇f(x^*)=0 and the Hessian ∇^2f(x^*) is ...

PieChart (Built-in Mathematica Symbol)

PieChart[{y_1, y_2, ...}] makes a pie chart with sector angle proportional to y_1, y_2, ....PieChart[{..., w_i[y_i, ...], ..., w_j[y_j, ...], ...}] makes a pie chart with ...

EstimatedDistribution (Built-in Mathematica Symbol)

EstimatedDistribution[data, dist] estimates the parametric distribution dist from data.EstimatedDistribution[data, dist, {{p, p_0}, {q, q_0}, ...}] estimates the parameters ...