PERTDistribution (Built-in Mathematica Symbol)

PERTDistribution[{min, max}, c] represents a PERT distribution with range min to max and maximum at c.PERTDistribution[{min, max}, c, \[Lambda]] represents a modified PERT ...

Random Number Generation (Mathematica Tutorial)

The ability to generate pseudorandom numbers is important for simulating events, estimating probabilities and other quantities, making randomized assignments or selections, ...

ProbabilityDistribution (Built-in Mathematica Symbol)

ProbabilityDistribution[pdf, {x, x_min, x_max}] represents the continuous distribution with PDF pdf in the variable x where the pdf is taken to be zero for x < x_min and x > ...

SmoothHistogram3D (Built-in Mathematica Symbol)

SmoothHistogram3D[{{x_1, y_1}, {x_2, y_2}, ...}] plots a 3D smooth kernel histogram of the values {x_i, y_i}.SmoothHistogram3D[{{x_1, y_1}, {x_2, y_2}, ...}, espec] plots a ...

GammaDistribution (Built-in Mathematica Symbol)

GammaDistribution[\[Alpha], \[Beta]] represents a gamma distribution with shape parameter \[Alpha] and scale parameter \[Beta].GammaDistribution[\[Alpha], \[Beta], \[Gamma], ...

NIntegrate (Built-in Mathematica Symbol)

NIntegrate[f, {x, x_min, x_max}] gives a numerical approximation to the integral \[Integral]_x_min^x_max\ f\ d \ x. NIntegrate[f, {x, x_min, x_max}, {y, y_min, y_max}, ...] ...

Integrate (Built-in Mathematica Symbol)

Integrate[f, x] gives the indefinite integral \[Integral]f d x. Integrate[f, {x, x_min, x_max}] gives the definite integral \[Integral]_x_min^x_max\ f\ d x. Integrate[f, {x, ...

DiracDelta (Built-in Mathematica Symbol)

DiracDelta[x] represents the Dirac delta function \[Delta](x). DiracDelta[x_1, x_2, ...] represents the multidimensional Dirac delta function \[Delta](x_1, x_2, ...).

WaveletMapIndexed (Built-in Mathematica Symbol)

WaveletMapIndexed[f, wd] applies the function f to the arrays of coefficients and indices of a ContinuousWaveletData or DiscreteWaveletData object.WaveletMapIndexed[f, dwd, ...

Partitioning Data into Clusters (Mathematica Tutorial)

Cluster analysis is an unsupervised learning technique used for classification of data. Data elements are partitioned into groups called clusters that represent proximate ...