WaringYuleDistribution[\[Alpha]] represents the Yule distribution with shape parameter \[Alpha].WaringYuleDistribution[\[Alpha], \[Beta]] represents the Waring distribution ...
Evaluate[expr] causes expr to be evaluated even if it appears as the argument of a function whose attributes specify that it should be held unevaluated.
GeneralizedLinearModelFit[{y_1, y_2, ...}, {f_1, f_2, ...}, x] constructs a generalized linear model of the form g -1 (\[Beta]_0 + \[Beta]_1 f_1 + \[Beta]_2 f_2 + ...) that ...
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 ...
LogitModelFit[{y_1, y_2, ...}, {f_1, f_2, ...}, x] constructs a binomial logistic regression model of the form 1/(1 + E -(\[Beta]_0 + \[Beta]_1 f_1 + \[Beta]_2 f_2 + \ ...)) ...
ProbitModelFit[{y_1, y_2, ...}, {f_1, f_2, ...}, x] constructs a binomial probit regression model of the form 1/2 (1 + erf((\[Beta]_0 + \[Beta]_1 f_1 + \[Beta]_2 f_2 + \ ...
ArrayRules[SparseArray[...]] gives the rules {pos_1 -> val_1, pos_2 -> val_2, ...} specifying elements in a sparse array. ArrayRules[list] gives rules for SparseArray[list].
ForAll
(Built-in Mathematica Symbol) ForAll[x, expr] represents the statement that expr is True for all values of x. ForAll[x, cond, expr] states that expr is True for all x satisfying the condition cond. ...
None
(Built-in Mathematica Symbol) None is a setting used for certain options.
In three dimensions, just as in two dimensions, you can give various graphics directives to specify how the different elements in a graphics object should be rendered. All ...