stapreg-methods.RdThe methods documented on this page are actually some of the least important methods defined for stapreg objects. The most important methods are documented separately, each with its own page. Links to those pages are provided in the See Also section, below.
# S3 method for stapreg coef(object, ...) # S3 method for stapreg confint(object, ...) # S3 method for stapreg fitted(object, ...) # S3 method for stapreg nobs(object, ...) # S3 method for stapreg nstap(object) # S3 method for stapreg ntap(object) # S3 method for stapreg nsap(object) # S3 method for stapreg nfix(object, ...) # S3 method for stapreg residuals(object, ...) # S3 method for stapreg se(object, ...) # S3 method for stapreg vcov(object, correlation = FALSE, ...) # S3 method for stapreg fixef(object, ...) # S3 method for stapreg ngrps(object, ...) # S3 method for stapreg ranef(object, ...) # S3 method for stapreg sigma(object, ...) # S3 method for stapreg VarCorr(x, sigma = 1, ...)
| object, x | A fitted model object returned by one of the
rstap modeling functions. See |
|---|---|
| ... | Ignored |
| correlation | For |
| sigma | Ignored (included for compatibility with
|
The methods documented on this page are similar to the methods defined for objects of class 'lm', 'glm', 'glmer', etc. However there are a few key differences:
residualsResiduals are always of type "response" (not "deviance"
residuals or any other type).
coefMedians are used for point estimates. See the Point estimates section
in print.stapreg for more details.
seThe se function returns standard errors based on
mad. See the Uncertainty estimates section in
print.stapreg for more details.
confintconfint will throw an error because the
posterior_interval function should be used to compute Bayesian
uncertainty intervals.
The print,
summary, and prior_summary
methods for stapreg objects for information on the fitted model.
The plot method to plot estimates and
diagnostics.
The posterior_predict and predictive_error
methods for predictions and predictive errors - can be used for posterior predictive checks.
The posterior_interval and predictive_interval
methods for uncertainty intervals for model parameters and predictions.
log_lik method for computing the log-likelihood
of (possibly new) data.
The as.matrix, as.data.frame,
and as.array methods to access posterior draws.