DifferenceDelta[f, i] gives the discrete difference \[DifferenceDelta]_i f = f(i + 1) - f(i).DifferenceDelta[f, {i, n}] gives the multiple difference DifferenceDelta[f, {i, ...

DirichletDistribution[{\[Alpha]_1, ..., \[Alpha] k +1}] represents a Dirichlet distribution of dimension k with shape parameters \[Alpha]_i.

FinancialBond[params, ambientparams] gives the value of a financial bond instrument.FinancialBond[params, ambientparams, prop] computes the specified property prop.

GompertzMakehamDistribution[\[Lambda], \[Xi]] represents a Gompertz distribution with scale parameter \[Lambda] and frailty parameter ...

GraphPlot[{v i 1 -> v j 1, v i 2 -> v j 2, ...}] generates a plot of the graph in which vertex v_ik is connected to vertex v_jk.GraphPlot[{{v i 1 -> v j 1, lbl_1}, ...}] ...

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 + \ ...)) ...

MaxStableDistribution[\[Mu], \[Sigma], \[Xi]] represents a generalized maximum extreme value distribution with location parameter \[Mu], scale parameter \[Sigma], and shape ...

Moment[list, r] gives the r\[Null]^th sample moment of the elements in list.Moment[dist, r] gives the r\[Null]^th moment of the symbolic distribution dist.Moment[..., {r_1, ...

NExpectation[expr, x \[Distributed] dist] gives the numerical expectation of expr under the assumption that x follows the probability distribution dist.NExpectation[expr, ...

PDF[dist, x] gives the probability density function for the symbolic distribution dist evaluated at x.PDF[dist, {x_1, x_2, ...}] gives the multivariate probability density ...