Interpolation[{f_1, f_2, ...}] constructs an interpolation of the function values f_i, assumed to correspond to x values 1, 2, ... . Interpolation[{{x_1, f_1}, {x_2, f_2}, ...

WeibullDistribution[\[Alpha], \[Beta]] represents a Weibull distribution with shape parameter \[Alpha] and scale parameter \[Beta].WeibullDistribution[\[Alpha], \[Beta], ...

Tensors are mathematical objects that give generalizations of vectors and matrices. In Mathematica, a tensor is represented as a set of lists, nested to a certain number of ...

In three dimensions, just as in two dimensions, you can give various graphics directives to specify how the different elements in a graphics object should be rendered. All ...

The names of built-in functions follow some general guidelines. The main expression or object on which a built-in function acts is usually given as the first argument to the ...

PrincipalComponents[matrix] transforms elements of matrix into unscaled principal components.

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. ...

Building on Mathematica's strengths in large-scale data handling, numerical optimization, and geometric computation, Version 6.0 brought a new level of automation to data ...

The ability to generate pseudorandom numbers is important for simulating events, estimating probabilities and other quantities, making randomized assignments or selections, ...

Catch[expr] returns the argument of the first Throw generated in the evaluation of expr. Catch[expr, form] returns value from the first Throw[value, tag] for which form ...