# Bayesian Time Series Modeling with Stan

## Documentation for package ‘bayesforecast’ version 1.0.5

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

A B C D E F G H I J L M N O P R S U V W

bayesforecast-package | Bayesian Time Series Modeling with 'Stan'.

## -- A --

aic | Computes posterior sample of the point wise AIC method from a 'varstan' object
AICc | Computes posterior sample of the point wise corrected AIC method from a 'varstan' object
air | Air Transport Passengers Australia
as.stan | Convert to a stanfit object.
aust | International Tourists to Australia: Total visitor nights.
auto.sarima | Automatic estimate of a Seasonal ARIMA model
autoplot.ts | Automatically create a ggplot for time series objects.
autoplot.varstan | autoplot methods for varstan models.

## -- B --

bayesforecast | Bayesian Time Series Modeling with 'Stan'.
bayes_factor | Bayes Factors from Marginal Likelihoods.
bayes_factor.varstan | Bayes Factors from Marginal Likelihoods.
beta | Define a beta prior distribution
bic | Computes posterior sample of the pointwise BIC method from a varstan object
birth | U.S. Monthly Live Births.
bridge_sampler | Log Marginal Likelihood via Bridge Sampling.
bridge_sampler.varstan | Log Marginal Likelihood via Bridge Sampling.

## -- C --

cauchy | Define a Cauchy prior distribution
check_residuals | Visual check of residuals in a 'varstan' object.
chisq | Define a chi square prior distribution

## -- D --

demgbp | DEM/GBP exchange rate log-returns

## -- E --

exponential | Define an exponential prior distribution
extract_stan | Extract chains of an 'stanfit' object implemented in 'rstan' package

## -- F --

fitted.varstan | Expected Values of the Posterior Predictive Distribution
forecast | Forecasting 'varstan' objects.
forecast.varstan | Forecasting 'varstan' objects.
fortify.ts | Automatically create a ggplot for time series objects.
fourier | Fourier terms for modeling seasonality.

## -- G --

gamma | Define a gamma prior distribution
garch | A constructor for a GARCH(s,k,h) model.
get_parameters | Get parameters of a 'varstan' object.
get_prior | Get the prior distribution of a model parameter
ggacf | 'acf' plot
gghist | Histogram with optional normal density functions
ggnorm | 'qqplot' with normal 'qqline'
ggpacf | 'pacf' plot.

## -- H --

Holt | A constructor for a Holt trend state-space model.
Hw | A constructor for a Holt-Winters state-space model.

## -- I --

inverse.chisq | Define an inverse gamma prior distribution
inverse.gamma | Define an inverse gamma prior distribution
ipc | Monthly inflation coefficients from 1980-2018.

## -- J --

jeffrey | Define a non informative Jeffrey's prior for the degree freedom hyper parameter

## -- L --

laplace | Define a Laplace prior distribution
LKJ | Define a LKJ matrix prior distribution
LocalLevel | A constructor for local level state-space model.
loglik | Extract posterior sample of the accumulated log-likelihood from a 'varstan' object
log_lik | Extract posterior sample of the point wise log-likelihood from a 'varstan' object.
log_lik.varstan | Extract posterior sample of the point wise log-likelihood from a 'varstan' object.
loo | Leave-one-out cross-validation
loo.varstan | Leave-one-out cross-validation

## -- M --

mcmc_plot | MCMC Plots Implemented in 'bayesplot'
mcmc_plot.varstan | MCMC Plots Implemented in 'bayesplot'
model | Print the defined model of a 'varstan' object.
model.Bekk | Print the defined model of a 'varstan' object.
model.garch | Print the defined model of a 'varstan' object.
model.Sarima | Print the defined model of a 'varstan' object.
model.SVM | Print the defined model of a 'varstan' object.
model.varma | Print the defined model of a 'varstan' object.
model.varstan | Print the defined model of a 'varstan' object.

## -- N --

naive | Naive and Random Walk models.
normal | Define a normal prior distribution

## -- O --

oildata | Annual oil production in Saudi Arabia

## -- P --

plot.varstan | plot methods for varstan models.
posterior_epred | Expected Values of the Posterior Predictive Distribution
posterior_epred.varstan | Expected Values of the Posterior Predictive Distribution
posterior_interval | Posterior uncertainty intervals
posterior_predict | Draw from posterior predictive h steps ahead distribution
posterior_predict.varstan | Draw from posterior predictive h steps ahead distribution
predictive_error | Out-of-sample predictive errors
predictive_error.varstan | Out-of-sample predictive errors
print.garch | Print a 'garch' model
print.Holt | Prints a Holt model.
print.Hw | Print a Holt-Winter model
print.LocalLevel | Print a Local Level model
print.naive | Print a 'naive' model
print.Sarima | Print a 'Sarima' model.
print.ssm | Print a state-space model.
print.SVM | Print a Stochastic Volatility model
print.varstan | Print a 'varstan' object
prior_summary | Generic function for extracting information about prior distributions
prior_summary.varstan | Generic function for extracting information about prior distributions

## -- R --

report | Print a full report of the time series model in a 'varstan' object.
report.Bekk | Print a full report of the time series model in a 'varstan' object.
report.garch | Print a full report of the time series model in a 'varstan' object.
report.naive | Print a full report of the time series model in a 'varstan' object.
report.Sarima | Print a full report of the time series model in a 'varstan' object.
report.varma | Print a full report of the time series model in a 'varstan' object.
report.varstan | Print a full report of the time series model in a 'varstan' object.
residuals.varstan | Generic function and method for extract the residual of a 'varstan' object

## -- S --

Sarima | Constructor a Multiplicative Seasonal ARIMA model.
set_prior | Set a prior distribution to a model parameter.
ssm | A constructor for a Additive linear State space model.
stan_garch | Fitting for a GARCH(s,k,h) model.
stan_Holt | Fitting an Holt state-space model.
stan_Hw | Fitting a Holt-Winters state-space model.
stan_LocalLevel | Fitting a Local level state-space model.
stan_naive | Naive and Random Walk models.
stan_sarima | Fitting a Multiplicative Seasonal ARIMA model.
stan_ssm | Fitting an Additive linear State space model.
stan_SVM | Fitting a Stochastic volatility model.
student | Define a t student prior distribution
summary.varstan | Summary method for a 'varstan' object
SVM | Constructor of an Stochastic volatility model object

## -- U --

uniform | Define a uniform prior distribution

## -- V --

varstan | Constructor of a 'varstan' object.

## -- W --

waic | Widely Applicable Information Criterion (WAIC)
waic.varstan | Widely Applicable Information Criterion (WAIC)