Bayesian Time Series Modeling with Stan


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Documentation for package ‘bayesforecast’ version 0.0.1

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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)