Predict from a zi_gec fit

Usage

# S3 method for class 'zi_gec'
predict(
  object,
  newdata = NULL,
  type = c("response", "zero", "intensity"),
  offset = NULL,
  se.fit = FALSE,
  interval = c("none", "confidence"),
  level = 0.95,
  ...
)

Arguments

object: A "zi_gec" object.
newdata: Optional covariate profiles. A zero_fe unit the fit has not seen, or every row when that column is absent, enters at the zero equation's reference unit; a unit with no positive count gets the structural-zero probability one, and one whose every count is positive zero (see compare_models(), Degrees of freedom).
type: "response" (marginal E(Y)), "zero" (structural-zero probability), or "intensity" (the count mean E of the GEC component).
offset: Optional offset (log scale) of the count component for the newdata rows; see predict.cpb().
se.fit, interval, level: Standard errors (se.fit = TRUE) and a level confidence interval (interval = "confidence") of the predicted quantity at the rows of newdata; see predict.cpb().
...: Unused.

Value

A numeric vector. With interval = "confidence", a matrix with columns fit, lwr and upr; with se.fit = TRUE, a list of fit (the vector or the matrix), se.fit and method (each row's interval source). Without se.fit, the source is the attribute method.