FindArgMax[f, x] gives the position x_max of a local maximum of f.FindArgMax[f, {x, x_0}] gives the position x_max of a local maximum of f, found by a search starting from ...
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 ...
KDistribution[\[Nu], w] represents a K distribution with shape parameters \[Nu] and w.
LocatorPane[{x, y}, back] represents a pane with a locator at position {x, y} and background back.LocatorPane[Dynamic[pt], back] takes the locator position to be the ...
LQOutputRegulatorGains[ss, {q, r}] gives the optimal state feedback gain matrix for the StateSpaceModel object ss and the quadratic cost function with output and control ...
MaxValue[f, x] gives the maximum value of f with respect to x.MaxValue[f, {x, y, ...}] gives the maximum value of f with respect to x, y, .... MaxValue[{f, cons}, {x, y, ...
NakagamiDistribution[\[Mu], \[Omega]] represents a Nakagami distribution with shape parameter \[Mu] and spread parameter \[Omega].
NMaximize[f, x] maximizes f numerically with respect to x.NMaximize[f, {x, y, ...}] maximizes f numerically with respect to x, y, .... NMaximize[{f, cons}, {x, y, ...}] ...
NMinimize[f, x] minimizes f numerically with respect to x.NMinimize[f, {x, y, ...}] minimizes f numerically with respect to x, y, .... NMinimize[{f, cons}, {x, y, ...}] ...
NSum
(Built-in Mathematica Symbol) NSum[f, {i, i_min, i_max}] gives a numerical approximation to the sum \[Sum]i = i_min i_max f.NSum[f, {i, i_min, i_max, di}] uses a step di in the sum.