Group Theory Algorithms (Mathematica Tutorial)

This tutorial introduces some basic algorithms for computing with finite permutation groups, other than those introduced in "Permutation Groups". A subgroup H of a group G ...

Integral Transforms and Related ... (Mathematica Tutorial)

One-dimensional Laplace transforms. The Laplace transform of a function f(t) is given by ∫_0^∞f(t)e^-stt. The inverse Laplace transform of F(s) is given for suitable γ by ( ...

CUDALink (CUDALink Guide)

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 ...

Creating Tables with Raw SQL (DatabaseLink Tutorial)

The raw SQL command CREATE TABLE creates tables in a database. An alternative is to use the Mathematica command SQLCreateTable, described in "Creating Tables". If you find ...

Precedence of Operators in Notations (Notation Package Tutorial)

The precedence of any new notation or operator is determined by examining the components from which it is constructed. For instance, +_ ℛ is grouped according to the ...

Variational Methods (Variational Methods Package Tutorial)

The basic problem of the calculus of variations is to determine the function u(x) that extremizes a functional F=∫_SubscriptBox[x^StyleBox[min, FontSlant -> Italic], ...

J/Link User Guide (JLink Overview)

Introduction to J/Link Calling Java from Mathematica Writing Java Programs That Use Mathematica

Definition Building Blocks (GUIKit Package Tutorial)

GUIKit definitions are defined as a hierarchy of widgets, whether they are defined in the Mathematica expression format or in the XML format, GUIKitXML. A single ...

DirectAgglomerate (Hierarchical Clustering Package Symbol)

DirectAgglomerate[m] constructs a cluster hierarchy based on the distance or dissimilarity matrix m.DirectAgglomerate[m, list] associates the elements of list with the rows ...

MeanTest (Hypothesis Testing Package Symbol)

MeanTest[list, \[Mu]_0] performs a test with null hypothesis \[Mu] = \[Mu]_0.