summary: summary

In dlmtree: Bayesian Treed Distributed Lag Models

summary

Description

summary generic function for S3method

Usage

summary(x, conf.level = 0.95, ...)

## S3 method for class 'hdlm'
summary(x, conf.level = 0.95, mcmc = FALSE, ...)

## S3 method for class 'hdlmm'
summary(x, conf.level = 0.95, mcmc = FALSE, ...)

## S3 method for class 'monotone'
summary(
  x,
  conf.level = 0.95,
  pred.at = NULL,
  cenval = 0,
  exposure.se = NULL,
  mcmc = FALSE,
  verbose = TRUE,
  ...
)

## S3 method for class 'tdlm'
summary(x, conf.level = 0.95, mcmc = FALSE, ...)

## S3 method for class 'tdlmm'
summary(
  x,
  conf.level = 0.95,
  marginalize = "mean",
  log10BF.crit = 0.5,
  mcmc = FALSE,
  verbose = TRUE,
  ...
)

## S3 method for class 'tdlnm'
summary(
  x,
  conf.level = 0.95,
  pred.at = NULL,
  cenval = 0,
  exposure.se = NULL,
  mcmc = FALSE,
  verbose = TRUE,
  ...
)

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.

Value

list of summary outputs of the model fit

dlmtree documentation built on June 8, 2025, 12:39 p.m.