WaveletThreshold (Built-in Mathematica Symbol)

WaveletThreshold[dwd] thresholds the detail wavelet coefficients in the DiscreteWaveletData object dwd.WaveletThreshold[dwd, tspec] thresholds the coefficients using the ...

Failure Recovery, Tracing, and Debugging (Parallel Package Tutorial)

A remote kernel in use may fail at any time, due to hardware, network, or software problems. A failure of a remote kernel will be noticed the next time Parallel Computing ...

Animate (Built-in Mathematica Symbol)

Animate[expr, {u, u_min, u_max}] generates an animation of expr in which u varies continuously from u_min to u_max. Animate[expr, {u, u_min, u_max, du}] takes u to vary in ...

EmpiricalDistribution (Built-in Mathematica Symbol)

EmpiricalDistribution[{x_1, x_2, ...}] represents an empirical distribution based on the data values x_i.EmpiricalDistribution[{{x_1, y_1, ...}, {x_2, y_2, ...}, ...}] ...

EstimatorGains (Built-in Mathematica Symbol)

EstimatorGains[ss, {p_1, p_2, ..., p_n}] gives the estimator gain matrix for the StateSpaceModel object ss, such that the poles of the estimator are p_i.

FindMaximum (Built-in Mathematica Symbol)

FindMaximum[f, x] searches for a local maximum in f, starting from an automatically selected point.FindMaximum[f, {x, x_0}] searches for a local maximum in f, starting from ...

FindMinimum (Built-in Mathematica Symbol)

FindMinimum[f, x] searches for a local minimum in f, starting from an automatically selected point.FindMinimum[f, {x, x_0}] searches for a local minimum in f, starting from ...

HypergeometricDistribution (Built-in Mathematica Symbol)

HypergeometricDistribution[n, n_succ, n_tot] represents a hypergeometric distribution.

ListAnimate (Built-in Mathematica Symbol)

ListAnimate[{expr_1, expr_2, ...}] generates an animation whose frames are the successive expr_i. ListAnimate[list, fps] displays fps frames per second.

LogLinearPlot (Built-in Mathematica Symbol)

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 ...