predict — predict • dlmtree

predict generic function for S3method

Usage

predict(
  x,
  new.data,
  new.exposure.data,
  ci.level = 0.95,
  type = "response",
  outcome = NULL,
  fixed.idx = list(),
  est.dlm = FALSE,
  verbose = TRUE,
  ...
)

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

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

Arguments

x: fitted dlmtree model with class 'hdlm', 'hdlmm'
new.data: new data frame which contains the same covariates and modifiers used to fit the model
new.exposure.data: new data frame/list which contains the same length of exposure lags used to fit the 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
...: not used

Value

list with the following elements:

ztg: posterior predictive mean of fixed effect
ztg.lims: lower/upper bound of posterior predictive distribution of fixed effect
dlmest: estimated exposure effect
dlmest.lower: lower bound of estimated exposure effect
dlmest.upper: upper bound of estimated exposure effect
fhat: posterior predictive mean of exposure effect
fhat.lims: lower/upper bound of posterior predictive distribution of exposure effect
y: posterior predictive mean
y.lims: lower/upper bound of posterior predictive distribution