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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