Model Predictions

Generate predictions from a temporal discounting binary choice model.

Usage

# S3 method for class 'td_bcnm'
predict(object, newdata = NULL, type = c("link", "response", "indiff"), ...)

Arguments

object

A temporal discounting binary choice model. See td_bcnm.

newdata

Optionally, a data frame to use for prediction. If omitted, the data used to fit the model will be used for prediction.

type

The type of prediction required. As in predict.glm, "link" (default) and "response" give predictions on the scales of the linear predictors and response variable, respectively. "indiff" gives predicted indifference points. For predicting indifference points, newdata needs only a del column.

...

Additional arguments currently not used.

Value

A vector of predictions.

See also

Other nonlinear binary choice model functions: coef.td_bcnm(), deviance.td_bcnm(), fitted.td_bcnm(), logLik.td_bcnm(), residuals.td_bcnm(), td_bcnm()

Examples

if (FALSE) { # \dontrun{
data("td_bc_single_ptpt")
mod <- td_bcnm(td_bc_single_ptpt, discount_function = 'hyperbolic')
indiffs <- predict(mod, newdata = data.frame(del = 1:100), type = 'indiff')
} # }