PascalDistribution (Built-in Mathematica Symbol)

PascalDistribution[n, p] represents a Pascal distribution with parameters n and p.

TriangularDistribution (Built-in Mathematica Symbol)

TriangularDistribution[{min, max}] represents a symmetric triangular statistical distribution giving values between min and max. TriangularDistribution[{min, max}, c] ...

TuringMachine (Built-in Mathematica Symbol)

TuringMachine[rule, init, t] generates a list representing the evolution of the Turing machine with the specified rule from initial condition init for t steps. ...

Naming and Finding Files (Mathematica Tutorial)

The precise details of the naming of files differ from one computer system to another. Nevertheless, Mathematica provides some fairly general mechanisms that work on all ...

Quasi-Newton Methods (Mathematica Tutorial)

There are many variants of quasi-Newton methods. In all of them, the idea is to base the matrix B_k in the quadratic model on an approximation of the Hessian matrix built up ...

Numerical Examples (Library Link Tutorial)

The functions accessible with Wolfram LibraryLink make it possible to optimize numerical computations while still keeping the flexibility and generality of Mathematica. If ...

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 ...

Statistical Plots Package (Statistical Plots Package Tutorial)

A wide variety of plots and charts are used to gain an overview of data from a statistical perspective. Some summarize statistical computations on the data, while others ...

Summary of New Features in 6.0 (Mathematica Guide)

Mathematica 6.0 fundamentally redefined Mathematica and introduced a major new paradigm for computation. Building on Mathematica's time-tested core symbolic architecture, ...

SurvivalDistribution (Built-in Mathematica Symbol)

SurvivalDistribution[{e_1, e_2, ...}] represents a survival distribution with event times e_i.SurvivalDistribution[{w_1, w_2, ...} -> {e_1, e_2, ...}] represents a survival ...