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.