Predict from a zi_cpb fit

Usage

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

Arguments

object: A "zi_cpb" object.
newdata: Data frame of 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, and a unit at a limit at that limit (see zero_fe in zi_cpb()); for the count equation's fe, see offset.
type: "response" for the marginal expected count E(Y), "zero" for the structural-zero probability, "intensity" for the mean of the CPB component (on the floor support, its rate lambda), or "rate" for the component's rate lambda.
offset: Optional offset (log scale) of the count component for the newdata rows; see predict.cpb(). With fe, a row whose fe column names a unit of the fit enters at that unit's count effect, a row of an unseen unit (or every row, when newdata has no fe column) at the reference unit, the mean effect of the units the data identify. A unit left out for having no positive count (see zi_cpb(), fe) predicts a mean of zero, and a structural-zero probability of NA where its own zero_fe dummy would be needed.
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.