FindArgMin[f, x] gives the position x_min of a local minimum of f.FindArgMin[f, {x, x_0}] gives the position x_min of a local minimum of f, found by a search starting from ...

FindMaxValue[f, x] gives the value at a local maximum of f.FindMaxValue[f, {x, x_0}] gives the value at a local maximum of f, found by a search starting from the point x = ...

Fit[data, funs, vars] finds a least-squares fit to a list of data as a linear combination of the functions funs of variables vars.

GatherBy[list, f] gathers into sublists each set of elements in list that gives the same value when f is applied.GatherBy[list, {f_1, f_2, ...}] gathers list into nested ...

GraphDistanceMatrix[g] gives the matrix of distances between vertices for the graph g.GraphDistanceMatrix[g, d] gives the matrix of distances between vertices of maximal ...

GroupOrbits[group, {p_1, ...}] returns the orbits of the points p_i under the action of the elements of group.GroupOrbits[group, {p_1, ...}, f] finds the orbits under the ...

HalfNormalDistribution[\[Theta]] represents a half-normal distribution with scale inversely proportional to parameter \[Theta].

HazardFunction[dist, x] gives the hazard function for the symbolic distribution dist evaluated at x.HazardFunction[dist, {x_1, x_2, ...}] gives the multivariate hazard ...

LevyDistribution[\[Mu], \[Sigma]] represents a Lévy distribution with location parameter \[Mu] and dispersion parameter \[Sigma].

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}, ...