Calculates predicted response for HDLMM — predict.hdlmm • dlmtree

Method for calculating predicted response for HDLMM

Usage

# S3 method for hdlmm
predict(
  object,
  new.data,
  new.exposure.data,
  ci.level = 0.95,
  type = "response",
  outcome = NULL,
  fixed.idx = list(),
  est.dlm = FALSE,
  verbose = TRUE,
  ...
)

Arguments

object: fitted dlmtree model with class hdlmm
new.data: new data frame which contains the same covariates and modifiers used to fit HDLMM model
new.exposure.data: new data frame/list which contains the same length of exposure lags used to fit HDLMM model
ci.level: credible interval level for posterior predictive distribution
type: type of prediction: "response" (default) or "waic". "waic" must be specified with `outcome` parameter
outcome: outcome required for WAIC calculation
fixed.idx: fixed index
est.dlm: flag for estimating dlm effect
verbose: TRUE (default) or FALSE: print output
...: additional parameters

Value

Posterior predictive distribution draws

Details

predict.hdlmm