Predict from a hurdle-CPB fit

Usage

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

Arguments

object: A "hurdle_cpb" object.
newdata: Data frame of covariate profiles (the intensity and participation covariates). A row of a fixed-effects unit the fit has not seen, or every row when the fe or part_fe column is absent, enters that equation at the reference unit, and a unit at a limit (no positive count, or no zero) at that limit (see part_fe in hurdle_cpb()).
type: "response" for the marginal expected count E(Y) (zeros included), "participation" for P(Y > 0), or "intensity" for E(Y | Y > 0).
offset: Optional offset (log scale) of the intensity for the newdata rows: a numeric vector or a column name in newdata; by default the fit's own offset column is read from newdata (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.