ClosenessCentrality[g] finds the closeness centrality.

CoefficientArrays[polys, vars] gives the arrays of coefficients of the variables vars in the polynomials polys.

DiscreteLQEstimatorGains[ss, {w, v}, \[Tau]] gives the optimal discrete-time estimator gain matrix with sampling period \[Tau] for the continuous-time StateSpaceModel object ...

ParameterEstimator is an option to EstimatedDistribution and FindDistributionParameters that specifies what parameter estimator to use.

Here is one way to get multiple minima: call NMinimize multiple times with different random seeds, which will cause different optimization paths to be taken. This defines a ...

Exact global optimization problems can be solved exactly using Minimize and Maximize. This computes the radius of the circle, centered at the origin, circumscribed about the ...

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

The Mathematica compiler can run computations in parallel. It does this by threading a compiled function over lists of data in parallel. A first step is to create a compiled ...

Mathematica 6.0 represented a major new level in Mathematica's distinguished twenty-year history of broad cutting-edge algorithm development. Mathematica's unified ...

ArrayQ[expr] gives True if expr is a full array or a SparseArray object, and gives False otherwise. ArrayQ[expr, patt] requires expr to be a full array with a depth that ...