D_discrete.margins: Calculate derivatives of marginal effects for binary...
In oglmx: Estimation of Ordered Generalized Linear Models

Description Usage Arguments Value Author(s) See Also

Calculates derivatives of marginal effects with respect to the estimated parameters for binary variables. Required to calculate standard errors of marginal effects.

D_discrete.margin_meanonly.mean(whichVars, whichXest, X, fouretas, link, std.dev)

D_discrete.margin_mean.var(whichZest, Z, fouretas, link, std.dev, gstd.dev)

D_discrete.margin_mean.alpha(estThresh, outcomematrix, fouretas, std.dev, link)

D_discrete.margin_var.mean(whichXest, X, fouretas, link, StdDevs)

D_discrete.margin_varonly.var(whichVars, whichZest, Z,fouretas, ZDinputs, link, 
                              StdDevs, gsdmodel)

D_discrete.margin_var.alpha(estThresh, outcomematrix, fouretas, StdDevs, link)

D_discrete.margin_meanvar.mean(whichXest, X, BothEqLocs, fouretas, StdDevs, link)

D_discrete.margin_meanvar.var(whichZest, Z, BothEqLocs, fouretas, ZDinputs, link,
                              StdDevs,gsdmodel)

`whichVars`	Numeric vector stating indexes of variables that are binary and marginal effects are desired.
`whichXest`	Logical vector indicating the variables in X for which the relevant parameters were estimated.
`X`	Data matrix containing variables in mean equation.
`fouretas`	Inputs to link functions.
`link`	specifies the link function for the estimated model.
`std.dev`	The calculated standard deviation of the error terms.
`Z`	Data matrix containing variables in variance equation.
`whichZest`	Logical vector indicating the variables in Z for which the relevant parameters were estimated.
`gstd.dev`	The calculated derivative of the standard deviation of the error terms.
`estThresh`	Logical vector indicating which threshold parameters were estimated.
`outcomematrix`	A matrix that indicates the outcome variable.
`ZDinputs`	Values of inputs to function that gives standard deviation when binary variable is equal to 0 and 1.
`StdDevs`	Values of standard deviation when binary variable is equal to 0 and 1.
`gsdmodel`	Expression used to calculate derivative of standard deviation.
`BothEqLocs`	Dataframe describing locations of binary variables that are in both the mean and variance equations.