probit.reg: Fit Probit Model.
In oglmx: Estimation of Ordered Generalized Linear Models

Description Usage Arguments Value Author(s) See Also

Wrapper function for oglmx to estimate the binary response probit model.

1 2	probit.reg(formula, data, start = NULL, weights=NULL, beta = NULL, analhessian = TRUE, na.action, savemodelframe = FALSE, robust = FALSE)

`formula`	an object of class `formula`: a symbolic description of the model used to explain the mean of the latent variable. The response variable should be a numeric vector or factor variable with two values.
`data`	a data frame containing the variables in the model.
`start`	either `NULL` or a numeric vector specifying start values for each of the estimated parameters, passed to the maximisation routine.
`weights`	either `NULL` or a numeric vector of length equal to the number of rows in the data frame. Used to apply weighted maximum likelihood estimation.
`beta`	`NULL` or numeric vector. Used to prespecify elements of the parameter vector for the equation of the mean of the latent variable. Vector should be of length one or of length equal to the number of explanatory variables in the mean equation. If of length one the value is presumed to correspond to the constant. If of length greater than one then `NA` should be entered for elements of the vector to be estimated.
`analhessian`	logical. Indicates whether the analytic Hessian should be calculated and used, default is TRUE, if set to FALSE a finite-difference approximation of the Hessian is used.
`na.action`	a function which indicates what should happen when the data contain NAs. The default is set by the `na.action` setting of `options`, and is `na.fail` if that is unset. The factory-fresh default is `na.omit`. Another possible value is `NULL`, no action. Value `na.exclude` can be useful.
`savemodelframe`	logical. Indicates whether the model frame(s) should be saved for future use. Default is `FALSE`. Should be switched to `TRUE` if intending to estimate Average Marginal Effects.
`robust`	logical. If set to `TRUE` the outer product or BHHH estimate of the meat in the sandwich of the variance-covariance matrix is calculated. If calculated standard errors will be calculated using the sandwich estimator by default when calling `summary`.