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bsts  

Bayesian Structural Time Series
View on CRAN: Click here


Download and install bsts package within the R console
Install from CRAN:
install.packages("bsts")

Install from Github:
library("remotes")
install_github("cran/bsts")

Install by package version:
library("remotes")
install_version("bsts", "0.9.11")



Attach the package and use:
library("bsts")
Maintained by
Steven L. Scott
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2014-06-27
Latest Update: 2025-09-03
Description:
Time series regression using dynamic linear models fit using MCMC. See Scott and Varian (2014) , among many other sources.
How to cite:
Steven L. Scott (2014). bsts: Bayesian Structural Time Series. R package version 0.9.11, https://cran.r-project.org/web/packages/bsts. Accessed 09 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:23), 0.5.1 (2014-06-27 13:56), 0.6.0 (2014-12-03 17:02), 0.6.1 (2014-12-05 01:22), 0.6.2 (2015-07-20 11:25), 0.6.3 (2016-03-15 16:10), 0.6.4 (2016-08-03 10:09), 0.6.5 (2016-08-19 00:51), 0.7.0 (2017-04-11 13:02), 0.7.1 (2017-05-28 10:30), 0.8.0 (2018-05-07 10:59), 0.9.0 (2019-05-22 00:20), 0.9.1 (2019-06-07 19:40), 0.9.2 (2019-09-22 19:40), 0.9.5 (2020-05-02 17:00), 0.9.6 (2021-04-07 11:40), 0.9.7 (2021-07-02 06:30), 0.9.8 (2022-05-30 09:00), 0.9.9 (2022-11-07 09:50), 0.9.10 (2024-01-17 14:02)
Other packages that cited bsts R package
View bsts citation profile
Other R packages that bsts depends, imports, suggests or enhances
Complete documentation for bsts
Functions, R codes and Examples using the bsts R package
Some associated functions: HarveyCumulator . MATCH.NumericTimestamps . StateSpecification . SuggestBurn . add.ar . add.dynamic.regression . add.local.level . add.local.linear.trend . add.monthly.annual.cycle . add.random.walk.holiday . add.seasonal . add.semilocal.linear.trend . add.shared.local.level . add.static.intercept . add.student.local.linear.trend . add.trig . aggregate.time.series . aggregate.weeks.to.months . auto.ar . bsts . bsts.options . compare.bsts.models . date.range . descriptive-plots . diagnostic-plots . dirm-model-options . dirm . estimate.time.scale . extend.time . format.timestamps . gdp . geometric.sequence . get.fraction . goog . holiday . iclaims . last.day.in.month . match.week.to.month . max.window.width . mbsts . mixed.frequency . month.distance . named.holidays . new.home.sales . one.step.prediction.errors . plot.bsts.mixed . plot.bsts . plot.bsts.prediction . plot.bsts.predictors . plot.holiday . plot.mbsts . plot.mbsts.prediction . predict.bsts . predict.mbsts . quarter . regression.holiday . regularize.timestamps . residuals.bsts . rsxfs . shark . shorten . simulate.fake.mixed.frequency.data . spike.slab.ar.prior . state.sizes . summary.bsts . to.posixt . turkish . week.ends . weekday.names . wide.to.long . 
Some associated R codes: add.ar.R . add.dynamic.regression.R . add.generalized.local.linear.trend.R . add.local.level.R . add.local.linear.trend.R . add.monthly.annual.cycle.R . add.random.walk.holiday.R . add.regression.holiday.R . add.seasonal.R . add.semilocal.linear.trend.R . add.static.intercept.R . add.student.local.linear.trend.R . add.trig.R . bsts.R . compare.bsts.models.R . date.functions.R . diagnostics.R . dirm.R . format.learning.data.R . format.timestamps.R . holiday.R . mbsts.R . mbsts.plots.R . mixed.frequency.R . plot_seasonal_effect.R . plots.R . predict.bsts.R . predict.mbsts.R . summary.bsts.R . utils.R .  Full bsts package functions and examples
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