summary: summary

Description

summary generic function for S3method

Usage

summary(x, conf.level = 0.95, ...)
# S3 method for hdlm
summary(x, conf.level = 0.95, mcmc = FALSE, ...)
# S3 method for hdlmm
summary(x, conf.level = 0.95, mcmc = FALSE, ...)
# S3 method for monotone
summary(
  x,
  conf.level = 0.95,
  pred.at = NULL,
  cenval = 0,
  exposure.se = NULL,
  mcmc = FALSE,
  verbose = TRUE,
  ...
)
# S3 method for tdlm
summary(x, conf.level = 0.95, mcmc = FALSE, ...)
# S3 method for tdlmm
summary(
  x,
  conf.level = 0.95,
  marginalize = "mean",
  log10BF.crit = 0.5,
  mcmc = FALSE,
  verbose = TRUE,
  ...
)
# S3 method for tdlnm
summary(
  x,
  conf.level = 0.95,
  pred.at = NULL,
  cenval = 0,
  exposure.se = NULL,
  mcmc = FALSE,
  verbose = TRUE,
  ...
)

Value

list of summary outputs of the model fit

Arguments

x: an object of class 'tdlm', 'tdlmm', 'tdlnm', 'hdlm', 'hdlmm', 'monotone'
conf.level: confidence level for computation of credible intervals
...: additional parameters
mcmc: keep all mcmc iterations (large memory requirement)
pred.at: numerical vector of exposure values to make predictions for at each time period
cenval: scalar exposure value that acts as a reference point for predictions at all other exposure values
exposure.se: scalar smoothing factor, if different from model
verbose: show progress in console
marginalize: value(s) for calculating marginal DLMs, defaults to "mean", can also specify a percentile from 1-99 for all other exposures, or a named vector with specific values for each exposure
log10BF.crit: Bayes Factor criteria for selecting exposures and interactions, such that log10(BayesFactor) > x. Default = 0.5.