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BetaPrimeDistribution   (Built-in Mathematica Symbol)
BetaPrimeDistribution[p, q] represents a beta prime distribution with shape parameters p and q. BetaPrimeDistribution[p, q, \[Beta]] represents a generalized beta prime ...
Graphics   (Built-in Mathematica Symbol)
Graphics[primitives, options] represents a two-dimensional graphical image.
SmoothHistogram   (Built-in Mathematica Symbol)
SmoothHistogram[{x_1, x_2, ...}] plots a smooth kernel histogram of the values x_i.SmoothHistogram[{x_1, x_2, ...}, espec] plots a smooth kernel histogram with estimator ...
PDB   (Mathematica Import/Export Format)
MIME type: chemical/x-pdb Protein Data Bank PDB files. 3D molecular model file. Used in bioinformatics applications and on the web for storing and exchanging molecule models. ...
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, ...}, ...
MardiaCombinedTest   (Built-in Mathematica Symbol)
MardiaCombinedTest[data] tests whether data follows a MultinormalDistribution using the Mardia combined test.MardiaCombinedTest[data, " property"] returns the value of " ...
ShapiroWilkTest   (Built-in Mathematica Symbol)
ShapiroWilkTest[data] tests whether data is normally distributed using the Shapiro\[Dash]Wilk test.ShapiroWilkTest[data, " property"] returns the value of " property".
ParametricPlot   (Built-in Mathematica Symbol)
ParametricPlot[{f_x, f_y}, {u, u_min, u_max}] generates a parametric plot of a curve with x and y coordinates f_x and f_y as a function of u. ParametricPlot[{{f_x, f_y}, ...
StationaryWaveletPacketTransform   (Built-in Mathematica Symbol)
StationaryWaveletPacketTransform[data] gives the stationary wavelet packet transform (SWPT) of an array of data.StationaryWaveletPacketTransform[data, wave] gives the ...
FindFit   (Built-in Mathematica Symbol)
FindFit[data, expr, pars, vars] finds numerical values of the parameters pars that make expr give a best fit to data as a function of vars. The data can have the form {{x_1, ...
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