PathGraph (Built-in Mathematica Symbol)

PathGraph[{v_1, v_2, ...}] yields a path with vertices v_i and edges between v_i and v i +\[ThinSpace]1 .PathGraph[{e_1, e_2, ...}] yields a path with edges ...

PetersenGraph (Built-in Mathematica Symbol)

PetersenGraph[n, k] gives the generalized Petersen graph P n, k.

Root (Built-in Mathematica Symbol)

Root[f, k] represents the exact k\[Null]^th root of the polynomial equation f[x] == 0. Root[{f, x_0}] represents the exact root of the general equation f[x] == 0 near x = ...

StableDistribution (Built-in Mathematica Symbol)

StableDistribution[type, \[Alpha], \[Beta], \[Mu], \[Sigma]] represents the stable distribution S_type with index of stability \[Alpha], skewness parameter \[Beta], location ...

UniformDistribution (Built-in Mathematica Symbol)

UniformDistribution[{min, max}] represents a continuous uniform statistical distribution giving values between min and max. UniformDistribution[] represents a uniform ...

WeightedAdjacencyGraph (Built-in Mathematica Symbol)

WeightedAdjacencyGraph[wmat] gives the graph with weighted adjacency matrix wmat.WeightedAdjacencyGraph[{v_1, v_2, ...}, wmat] gives the graph with vertices v_i and weighted ...

Library Structure and Life Cycle (Library Link Tutorial)

Wolfram LibraryLink allows dynamic libraries to be directly loaded into the Mathematica kernel so that functions in the libraries can be immediately called from Mathematica. ...

Configuring the Compilation (C Compiler Driver Package Tutorial)

The CCompilerDriver package lets you work with C compilers that are installed on your computer. It lets you build executables, libraries, and object files from C source code. ...

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 ...

FindDistributionParameters (Built-in Mathematica Symbol)

FindDistributionParameters[data, dist] finds the parameter estimates for the distribution dist from data.FindDistributionParameters[data, dist, {{p, p_0}, {q, q_0}, ...}] ...