Package: bayesforecast 1.0.1

bayesforecast: Bayesian Time Series Modeling with Stan

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>.

Authors:Asael Alonzo Matamoros [aut, cre], Cristian Cruz Torres [aut], Andres Dala [ctb], Rob Hyndman [ctb], Mitchell O'Hara-Wild [ctb]

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NEWS

# Install 'bayesforecast' in R:
install.packages('bayesforecast', repos = c('https://asael697.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/asael697/bayesforecast/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • air - Air Transport Passengers Australia
  • aust - International Tourists to Australia: Total visitor nights.
  • birth - U.S. Monthly Live Births.
  • demgbp - DEM/GBP exchange rate log-returns
  • ipc - Monthly inflation coefficients from 1980-2018.
  • oildata - Annual oil production in Saudi Arabia

On CRAN:

Conda:

bayesian-inferenceforecasting-modelsmcmcstantime-series-analysiscpp

6.92 score 45 stars 62 scripts 510 downloads 61 exports 110 dependencies

Last updated 1 years agofrom:9909f78d7f. Checks:1 OK, 11 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 23 2025
R-4.5-win-x86_64NOTEMar 23 2025
R-4.5-mac-x86_64NOTEMar 23 2025
R-4.5-mac-aarch64NOTEMar 23 2025
R-4.5-linux-x86_64NOTEMar 23 2025
R-4.4-win-x86_64NOTEMar 23 2025
R-4.4-mac-x86_64NOTEMar 23 2025
R-4.4-mac-aarch64NOTEMar 23 2025
R-4.4-linux-x86_64NOTEMar 23 2025
R-4.3-win-x86_64NOTEMar 23 2025
R-4.3-mac-x86_64NOTEMar 23 2025
R-4.3-mac-aarch64NOTEMar 23 2025

Exports:aicAICcas.stanauto.sarimaautoplotbayes_factorbetabicbridge_samplercauchycheck_residualschisqexponentialextract_stanforecastfouriergammagarchget_parametersget_priorggacfgghistggnormggpacfHoltHwinverse.chisqinverse.gammajeffreylaplaceLKJLocalLevellog_likloglikloomcmc_plotmodelnaivenormalposterior_epredposterior_intervalposterior_predictpredictive_errorprior_summaryreportSarimaset_priorssmstan_garchstan_Holtstan_Hwstan_LocalLevelstan_naivestan_sarimastan_ssmstan_SVMstudentSVMuniformvarstanwaic

Dependencies:abindastsabackportsbase64encbayesplotBHbridgesamplingBrobdingnagbslibcachemcallrcheckmateclicodacolorspacecpp11curldescdigestdistributionaldplyrdygraphsevaluateextraDistrfansifarverfastmapfontawesomeforecastfracdifffsgenericsggplot2ggridgesgluegridExtragtablehighrhtmltoolshtmlwidgetsinlineisobandjquerylibjsonliteknitrlabelinglatticelifecyclelmtestloolubridatemagrittrMASSMatrixmatrixStatsmemoisemgcvmimemunsellmvtnormnlmennetnumDerivpillarpkgbuildpkgconfigplyrposteriorprocessxprophetpspurrrquadprogquantmodQuickJSRR6rappdirsRColorBrewerRcppRcppArmadilloRcppEigenRcppParallelreshape2rlangrmarkdownrstanrstantoolssassscalesStanHeadersstringistringrtensorAtibbletidyrtidyselecttimechangetimeDatetinytextseriesTTRurcautf8vctrsviridisLitewithrxfunxtsyamlzoo

Estimating ARIMA Models

Daniel Dala and Asael Alonzo Matamoros

Rendered fromARIMA.Rmdusingknitr::rmarkdownon Mar 23 2025.

Last update: 2021-06-14
Started: 2021-03-04

Estimating GARCH Models

Asael Alonzo Matamoros and Andrés Dala

Rendered fromGARCH.Rmdusingknitr::rmarkdownon Mar 23 2025.

Last update: 2021-06-17
Started: 2021-03-04

Readme and manuals

Help Manual

Help pageTopics
Bayesian Time Series Modeling with 'Stan'.bayesforecast-package bayesforecast
Computes posterior sample of the pointwise AIC method from a varstan objectaic
Computes posterior sample of the pointwise corrected AIC method from a varstan objectAICc
Air Transport Passengers Australiaair
Convert to a stanfit object.as.stan
International Tourists to Australia: Total visitor nights.aust
Automatic estimate of a Seasonal ARIMA modelauto.sarima
Automatically create a ggplot for time series objects.autoplot.ts fortify.ts
autoplot methods for varstan models.autoplot.varstan
Bayes Factors from Marginal Likelihoods.bayes_factor bayes_factor.varstan
Define a beta prior distributionbeta
Computes posterior sample of the pointwise BIC method from a varstan objectbic
U.S. Monthly Live Births.birth
Log Marginal Likelihood via Bridge Sampling.bridge_sampler bridge_sampler.varstan
Define a Cauchy prior distributioncauchy
Visual check of residuals in a 'varstan' object.check_residuals
Define a chi square prior distributionchisq
DEM/GBP exchange rate log-returnsdemgbp
Define an exponential prior distributionexponential
Extract chains of an stanfit object implemented in rstan packageextract_stan
Expected Values of the Posterior Predictive Distributionfitted.varstan
Forecasting varstan objectsforecast forecast.varstan
Fourier terms for modeling seasonality.fourier
Define a gamma prior distributiongamma
A constructor for a GARCH(s,k,h) model.garch
Get parameters of a varstan objectget_parameters
Get the prior distribution of a model parameterget_prior
'acf' plotggacf
Histogram with optional normal density functionsgghist
'qqplot' with normal 'qqline'ggnorm
'pacf' plot.ggpacf
A constructor for a Holt trend state-space model.Holt
A constructor for a Holt-Winters state-space model.Hw
Define an inverse gamma prior distributioninverse.chisq
Define an inverse gamma prior distributioninverse.gamma
Monthly inflation coefficients from 1980-2018.ipc
Define a non informative Jeffrey's prior for the degree freedom hyper parameterjeffrey
Define a Laplace prior distributionlaplace
Define a LKJ matrix prior distributionLKJ
A constructor for local level state-space model.LocalLevel
Extract posterior sample of the pointwise log-likelihood from a varstan object.log_lik log_lik.varstan
Extract posterior sample of the accumulated log-likelihood from a varstan objectloglik
Leave-one-out cross-validationloo loo.varstan
MCMC Plots Implemented in 'bayesplot'mcmc_plot mcmc_plot.varstan
Print the defined model of a varstan object.model model.Bekk model.garch model.Sarima model.SVM model.varma model.varstan
Naive and Random Walk models.naive
Define a normal prior distributionnormal
Annual oil production in Saudi Arabiaoildata
plot methods for varstan models.plot.varstan
Expected Values of the Posterior Predictive Distributionposterior_epred posterior_epred.varstan
Posterior uncertainty intervalsposterior_interval
Draw from posterior predictive h steps ahead distributionposterior_predict posterior_predict.varstan
Out-of-sample predictive errorspredictive_error predictive_error.varstan
Print a garch modelprint.garch
Print a Holt modelprint.Holt
Print a Holt-Winter modelprint.Hw
Print a Local Level modelprint.LocalLevel
Print a naive modelprint.naive
Print a Sarima modelprint.Sarima
Print a state-space modelprint.ssm
Print a Stochastic Volatility modelprint.SVM
Print a varstan objectprint.varstan
Generic function for extracting information about prior distributionsprior_summary prior_summary.varstan
Print a full report of the time series model in a varstan object.report report.Bekk report.garch report.naive report.Sarima report.varma report.varstan
Generic function and method for extract the residual of a varstan objectresiduals.varstan
Constructor a Multiplicative Seasonal ARIMA model.Sarima
Set a prior distribution to a model parameter.set_prior
A constructor for a Additive linear State space model.ssm
Fitting for a GARCH(s,k,h) model.stan_garch
Fitting an Holt state-space model.stan_Holt
Fitting a Holt-Winters state-space model.stan_Hw
Fitting a Local level state-space model.stan_LocalLevel
Naive and Random Walk models.stan_naive
Fitting a Multiplicative Seasonal ARIMA model.stan_sarima
Fitting an Additive linear State space model.stan_ssm
Fitting a Stochastic volatility modelstan_SVM
Define a t student prior distributionstudent
Summary method for a varstan objectsummary.varstan
Constructor of an Stochastic volatility model objectSVM
Define a uniform prior distributionuniform
Constructor of a varstan object.varstan
Widely Applicable Information Criterion (WAIC)waic waic.varstan