TransformedDistribution (Built-in Mathematica Symbol)

TransformedDistribution[expr, x \[Distributed] dist] represents the transformed distribution of expr where the random variable x follows the distribution ...

MovingAverage (Built-in Mathematica Symbol)

MovingAverage[list, r] gives the moving average of list, computed by averaging runs of r elements.MovingAverage[list, {w_1, w_2, ..., w_r}] gives the moving average of list, ...

OutputControllableModelQ (Built-in Mathematica Symbol)

OutputControllableModelQ[ss] gives True if the StateSpaceModel object ss is output controllable, and False otherwise.

RandomImage (Built-in Mathematica Symbol)

RandomImage[max, {w, h}] gives an image of dimensions {w, h} with pseudorandom pixel values generated from a uniform distribution in the range 0 to max.RandomImage[{min, ...

KernelMixtureDistribution (Built-in Mathematica Symbol)

KernelMixtureDistribution[{x_1, x_2, ...}] represents a kernel mixture distribution based on the data values x_i.KernelMixtureDistribution[{{x_1, y_1, ...}, {x_2, y_2, ...}, ...

Image Processing (Mathematica Tutorial)

Mathematica provides built-in support for both programmatic and interactive image processing, fully integrated with Mathematica's powerful mathematical and algorithmic ...

ListConvolve (Built-in Mathematica Symbol)

ListConvolve[ker, list] forms the convolution of the kernel ker with list. ListConvolve[ker, list, k] forms the cyclic convolution in which the k\[Null]^th element of ker is ...

Numerical Nonlinear Local Optimization (Mathematica Tutorial)

Numerical algorithms for constrained nonlinear optimization can be broadly categorized into gradient-based methods and direct search methods. Gradient search methods use ...

KalmanEstimator (Built-in Mathematica Symbol)

KalmanEstimator[ss, {w, v}] constructs the Kalman estimator for the StateSpaceModel object ss with process and measurement noise covariance matrices w and v. ...

LeveneTest (Built-in Mathematica Symbol)

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, ...