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

aic | Computes posterior sample of the pointwise AIC method from a varstan object |

AICc | Computes posterior sample of the pointwise corrected AIC method from a varstan object |

as.stan | Convert to a stanfit object. |

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. |

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. |

cauchy | Define a Cauchy prior distribution |

check_residuals | Visual check of residuals in a 'varstan' object. |

chisq | Define a chi square prior distribution |

exponential | Define an exponential prior distribution |

extract_stan | Extract chains of an stanfit object implemented in rstan package |

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. |

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. |

inverse.chisq | Define an inverse gamma prior distribution |

inverse.gamma | Define an inverse gamma prior distribution |

ipc | Monthly inflation coefficients from 1980-2018. |

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

laplace | Define a Laplace prior distribution |

LKJ | Define a LKJ matrix prior distribution |

loglik | Extract posterior sample of the accumulated log-likelihood from a varstan object |

log_lik | Extract posterior sample of the pointwise log-likelihood from a varstan object. |

log_lik.varstan | Extract posterior sample of the pointwise log-likelihood from a varstan object. |

loo | Leave-one-out cross-validation |

loo.varstan | Leave-one-out cross-validation |

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. |

naive | Naive and Random Walk models. |

normal | Define a normal prior distribution |

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.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 |

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 |

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_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 |

uniform | Define a uniform prior distribution |

varstan | Constructor of a varstan object. |

waic | Widely Applicable Information Criterion (WAIC) |

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