discrete.margin_meanonly {oglmx} | R Documentation |
Calculate marginal effects for binary variables. Functions calculate for variables that are only in the mean equation, only in the variance equation, and variables in both.
discrete.margin_meanonly(beta, X, whichVars, etas, link, std.dev)
discrete.margin_varonly(delta, Z, whichVars, sdmodel, etas, link, std.dev)
discrete.margin_both(beta, X, delta, Z, BothEqLocs, sdmodel, etas, link, std.dev)
beta |
Coefficients for the mean equation. |
X |
Variable values for the mean equation. |
whichVars |
Numeric vector stating indexes of variables that are binary and marginal effects are desired. |
etas |
Inputs to link functions. |
link |
specifies the link function for the estimated model. |
std.dev |
The calculated standard deviation of the error terms. |
delta |
Coefficients for the variance equation. |
Z |
Variable values for the variance equation. |
sdmodel |
Expression used to calculate standard deviation. |
BothEqLocs |
Dataframe describing locations of binary variables that are in both the mean and variance equations. |
Numeric vector of marginal effects. Has as attributes calculated components that are used to calculate derivatives of marginal effects.
Nathan Carroll, nathan.carroll@ur.de