summary.mcmc_output  R Documentation 
This functions returns a data frame containing mean, standard deviations, standard errors, and effective sample size estimates for parameters and states.
## S3 method for class 'mcmc_output'
summary(
object,
return_se = FALSE,
variable = "theta",
probs = c(0.025, 0.975),
times,
states,
use_times = TRUE,
method = "sokal",
...
)
object 
Output from 
return_se 
if 
variable 
Are the summary statistics computed for either

probs 
A numeric vector defining the quantiles of interest. Default is

times 
A vector of indices. For states, for what time points the
summaries should be computed? Default is all, ignored if

states 
A vector of indices. For what states the summaries should be
computed?. Default is all, ignored if

use_times 
If 
method 
Method for computing integrated autocorrelation time. Default
is 
... 
Ignored. 
For ISMCMC two types of standard errors are reported. SEIS can be regarded as the square root of independent IS variance, whereas SE corresponds to the square root of total asymptotic variance (see Remark 3 of Vihola et al. (2020)).
If variable
is "theta"
or "states"
, a
data.frame
object. If "both"
, a list of two data frames.
Vihola, M, Helske, J, Franks, J. Importance sampling type estimators based on approximate marginal Markov chain Monte Carlo. Scand J Statist. 2020; 138. https://doi.org/10.1111/sjos.12492
data("negbin_model")
summary(negbin_model, return_se = TRUE, method = "geyer")
summary(negbin_model, times = c(1, 200), prob = c(0.05, 0.5, 0.95))
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