summary.varstan

object

A boolean value, if its <code>TRUE</code> it returns the median of the posterior distribution,
And if its <code>FALSE</code> it returns the mean, by default is the <code>FALSE</code> value

robust

A number \(p \in (0,1)\) indicating the desired
probability mass to include in the intervals. The default is to report
\(90\)% intervals (<code>prob=0.9</code>) rather than the traditionally used
\(95\)%.

prob

Further arguments passed to <code>summary</code>.

Summaries of parameter estimates and MCMC convergence diagnostics
(Monte Carlo error, effective sample size, Rhat).

Fit Bayesian time series models using 'Stan' for full Bayesian inference. A wide range
of distributions and models are supported, allowing users to fit Seasonal ARIMA, ARIMAX, Dynamic
Harmonic Regression, GARCH, t-student innovation GARCH models, asymmetric GARCH, Random Walks, stochastic
volatility models for univariate time series. Prior specifications are flexible and explicitly encourage
users to apply prior distributions that actually reflect their beliefs. Model fit can easily be assessed
and compared with typical visualization methods, information criteria such as loglik, AIC, BIC WAIC, Bayes
factor and leave-one-out cross-validation methods. References: Hyndman (2017)
<doi:10.18637/jss.v027.i03>; Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>.

Asael Alonzo Matamoros

summary.varstan: Summary method for a varstan object

Description

Usage

Arguments

Value