A stanreg, stanfit, brmsfit, blavaan, or MCMCglmm object.
...
Currently not used.
effects
Should results for fixed effects, random effects or both be
returned? Only applies to mixed models. May be abbreviated.
component
Should results for all parameters, parameters for the
conditional model or the zero-inflated part of the model be returned? May
be abbreviated. Only applies to brms-models.
parameters
Regular expression pattern that describes the parameters
that should be returned. Meta-parameters (like lp__ or prior_) are
filtered by default, so only parameters that typically appear in the
summary() are returned. Use parameters to select specific parameters
for the output.
Details
Monte Carlo Standard Error (MCSE) is another measure of
accuracy of the chains. It is defined as standard deviation of the chains
divided by their effective sample size (the formula for mcse() is
from Kruschke 2015, p. 187). The MCSE “provides a quantitative
suggestion of how big the estimation noise is”.
References
Kruschke, J. (2014). Doing Bayesian data analysis: A tutorial with R, JAGS, and Stan. Academic Press.