Simplify (Built-in Mathematica Symbol)

Simplify[expr] performs a sequence of algebraic and other transformations on expr, and returns the simplest form it finds. Simplify[expr, assum] does simplification using ...

Combinatorial Functions (Mathematica Tutorial)

Combinatorial functions. The factorial function n! gives the number of ways of ordering n objects. For non-integer n, the numerical value of n! is obtained from the gamma ...

Compiling Mathematica Expressions (Mathematica Tutorial)

If you make a definition like f[x_]:=x Sin[x], Mathematica will store the expression x Sin[x] in a form that can be evaluated for any x. Then when you give a particular value ...

Some General Notations and Conventions (Mathematica Tutorial)

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 ...

Special Characters (Mathematica Tutorial)

Built into Mathematica are a large number of special characters intended for use in mathematical and other notation. "Listing of Named Characters" gives a complete listing. ...

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 ...

Inserting Data with Raw SQL (DatabaseLink Tutorial)

The SQL command INSERT inserts data into a database. An alternative is to use the Mathematica command SQLInsert, as described in "Inserting Data". If you find that the ...

Introduction to J/Link (JLink Tutorial)

Welcome to J/Link, a product that integrates Mathematica and Java. J/Link lets you call Java from Mathematica in a completely transparent way, and it also lets you use and ...

FinancialBond (Built-in Mathematica Symbol)

FinancialBond[params, ambientparams] gives the value of a financial bond instrument.FinancialBond[params, ambientparams, prop] computes the specified property prop.

LogitModelFit (Built-in Mathematica Symbol)

LogitModelFit[{y_1, y_2, ...}, {f_1, f_2, ...}, x] constructs a binomial logistic regression model of the form 1/(1 + E -(\[Beta]_0 + \[Beta]_1 f_1 + \[Beta]_2 f_2 + \ ...)) ...