DiracDelta[x] represents the Dirac delta function \[Delta](x). DiracDelta[x_1, x_2, ...] represents the multidimensional Dirac delta function \[Delta](x_1, x_2, ...).
FindShortestTour[{e_1, e_2, ...}] attempts to find an ordering of the e_i that minimizes the total distance on a tour that visits all the e_i once.
HeavisideTheta[x] represents the Heaviside theta function \[Theta](x), equal to 0 for x < 0 and 1 for x > 0. HeavisideTheta[x_1, x_2, ...] represents the multidimensional ...
MardiaKurtosisTest[data] tests whether data follows a MultinormalDistribution using the Mardia kurtosis test.MardiaKurtosisTest[data, " property"] returns the value of " ...
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. ...
ArcSinDistribution[{x min, x max}] represents the arc sine distribution supported between x min and x max.
LinearProgramming[c, m, b] finds a vector x that minimizes the quantity c.x subject to the constraints m.x >= b and x >= 0. LinearProgramming[c, m, {{b_1, s_1}, {b_2, s_2}, ...
Minors
(Built-in Mathematica Symbol) Minors[m] gives the minors of a matrix m. Minors[m, k] gives the k\[Null]\[Null]^th minors.
Orthogonalize[{v_1, v_2, ...}] gives an orthonormal basis found by orthogonalizing the vectors v_i.Orthogonalize[{e_1, e_2, ...}, f] gives a basis for the e_i orthonormal ...
RandomVariate[dist] gives a pseudorandom variate from the symbolic distribution dist.RandomVariate[dist, n] gives a list of n pseudorandom variates from the symbolic ...