DynamicModule (Built-in Mathematica Symbol)

DynamicModule[{x, y, ...}, expr] represents an object which maintains the same local instance of the symbols x, y, ... in the course of all evaluations of Dynamic objects in ...

Set (Built-in Mathematica Symbol)

lhs = rhs evaluates rhs and assigns the result to be the value of lhs. From then on, lhs is replaced by rhs whenever it appears. {l_1, l_2, ...} = {r_1, r_2, ...} evaluates ...

Extrapolation Method for NDSolve (Mathematica Tutorial)

Extrapolation methods are a class of arbitrary-order methods with automatic order and step-size control. The error estimate comes from computing a solution over an interval ...

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 ...

SectorChart (Built-in Mathematica Symbol)

SectorChart[{{x_1, y_1}, {x_1, y_2}, ...}] makes a sector chart with sector angles proportional to x_i and radii y_i.SectorChart[{..., w_i[{x_i, y_i}, ...], ..., w_j[{x_j, ...

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, ...

GeneralizedLinearModelFit (Built-in Mathematica Symbol)

GeneralizedLinearModelFit[{y_1, y_2, ...}, {f_1, f_2, ...}, x] constructs a generalized linear model of the form g -1 (\[Beta]_0 + \[Beta]_1 f_1 + \[Beta]_2 f_2 + ...) that ...

NonlinearModelFit (Built-in Mathematica Symbol)

NonlinearModelFit[{y_1, y_2, ...}, form, {\[Beta]_1, ...}, x] constructs a nonlinear model with structure form that fits the y_i for successive x values 1, 2, ... using the ...

TruncatedDistribution (Built-in Mathematica Symbol)

TruncatedDistribution[{x_min, x_max}, dist] represents the distribution obtained by truncating the values of dist to lie between x_min and ...

Linear Programming (Mathematica Tutorial)

Linear programming problems are optimization problems where the objective function and constraints are all linear. Mathematica has a collection of algorithms for solving ...