predict generic function for S3method
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 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 hdlmm
predict(
x,
new.data,
new.exposure.data,
ci.level = 0.95,
type = "response",
outcome = NULL,
fixed.idx = list(),
est.dlm = FALSE,
verbose = TRUE,
...
)
list with the following elements:
posterior predictive mean of fixed effect
lower/upper bound of posterior predictive distribution of fixed effect
estimated exposure effect
lower bound of estimated exposure effect
upper bound of estimated exposure effect
posterior predictive mean of exposure effect
lower/upper bound of posterior predictive distribution of exposure effect
posterior predictive mean
lower/upper bound of posterior predictive distribution
fitted dlmtree model with class 'hdlm', 'hdlmm'
new data frame which contains the same covariates and modifiers used to fit the model
new data frame/list which contains the same length of exposure lags used to fit the model
credible interval level for posterior predictive distribution
type of prediction: "response" (default) or "waic". "waic" must be specified with `outcome` parameter
outcome required for WAIC calculation
fixed index
flag for estimating dlm effect
TRUE (default) or FALSE: print output
not used