KalmanEstimator[ss, {w, v}] constructs the Kalman estimator for the StateSpaceModel object ss with process and measurement noise covariance matrices w and v. ...
LeveneTest[data] tests whether the variance of data is 1. LeveneTest[{data_1, data_2}] tests whether the variances of data_1 and data_2 are equal.LeveneTest[dspec, ...
ListAnimate[{expr_1, expr_2, ...}] generates an animation whose frames are the successive expr_i. ListAnimate[list, fps] displays fps frames per second.
ListInterpolation[array] constructs an InterpolatingFunction object that represents an approximate function that interpolates the array of values given. ...
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 ...
LogLinearPlot[f, {x, x_min, x_max}] generates a log-linear plot of f as a function of x from x_min to x_max. LogLinearPlot[{f_1, f_2, ...}, {x, x_min, x_max}] generates ...
LogLogisticDistribution[\[Gamma], \[Sigma]] represents a log-logistic distribution with shape parameter \[Gamma] and scale parameter \[Sigma].
MatrixExp[m] gives the matrix exponential of m. MatrixExp[m, v] gives the matrix exponential of m applied to the vector v.
NyquistPlot[g] gives the Nyquist plot of a rational function g in one complex variable.NyquistPlot[sys] gives the Nyquist plot of a TransferFunctionModel or StateSpaceModel ...
PascalDistribution[n, p] represents a Pascal distribution with parameters n and p.