HyperbolicDistribution[\[Alpha], \[Beta], \[Delta], \[Mu]] represents a hyperbolic distribution with location parameter \[Mu], scale parameter \[Delta], shape parameter ...
JohnsonDistribution["SB", \[Gamma], \[Delta], \[Mu], \[Sigma]] represents a bounded Johnson distribution with shape parameters \[Gamma], \[Delta], location parameter \[Mu], ...
ListLinePlot[{y_1, y_2, ...}] plots a line through a list of values, assumed to correspond to x coordinates 1, 2, .... ListLinePlot[{{x_1, y_1}, {x_2, y_2}, ...}] plots a ...
NormalDistribution[\[Mu], \[Sigma]] represents a normal (Gaussian) distribution with mean \[Mu] and standard deviation \[Sigma].NormalDistribution[] represents a normal ...
WeibullDistribution[\[Alpha], \[Beta]] represents a Weibull distribution with shape parameter \[Alpha] and scale parameter \[Beta].WeibullDistribution[\[Alpha], \[Beta], ...
ListPlot[{y_1, y_2, ...}] plots points corresponding to a list of values, assumed to correspond to x coordinates 1, 2, .... ListPlot[{{x_1, y_1}, {x_2, y_2}, ...}] plots a ...
Mathematica has over 3000 built-in functions and other objects, all based on a single unified framework, and all carefully designed to work together, both in simple ...
CellularAutomaton[rule, init, t] generates a list representing the evolution of the cellular automaton with the specified rule from initial condition init for t steps. ...
PearsonDistribution[a_1, a_0, b_2, b_1, b_0] represents a distribution of the Pearson family with parameters a_1, a_0, b_2, b_1, and b_0.PearsonDistribution[type, a_1, a_0, ...
Linear programming problems are optimization problems where the objective function and constraints are all linear. Mathematica has a collection of algorithms for solving ...