bsts0.9.10 package

Bayesian Structural Time Series

add.ar

AR(p) state component

add.dynamic.regression

Dynamic Regression State Component

add.local.level

Local level trend state component

add.local.linear.trend

Local linear trend state component

add.monthly.annual.cycle

Monthly Annual Cycle State Component

add.random.walk.holiday

Random Walk Holiday State Model

add.seasonal

Seasonal State Component

add.semilocal.linear.trend

Semilocal Linear Trend

add.shared.local.level

Local level trend state component

add.static.intercept

Static Intercept State Component

add.student.local.linear.trend

Robust local linear trend

add.trig

Trigonometric Seasonal State Component

aggregate.time.series

Aggregate a fine time series to a coarse summary

aggregate.weeks.to.months

Aggregate a weekly time series to monthly

auto.ar

Sparse AR(p)

bsts-package

bsts

bsts.options

Bsts Model Options

bsts

Bayesian Structural Time Series

compare.bsts.models

Compare bsts models

date.range

Date Range

descriptive-plots

Descriptive Plots

diagnostic-plots

Diagnostic Plots

dirm-model-options

Specify Options for a Dynamic Intercept Regression Model

dirm

Dynamic intercept regression model

estimate.time.scale

Intervals between dates

extend.time

Extends a vector of dates to a given length

format.timestamps

Checking for Regularity

geometric.sequence

Create a Geometric Sequence

get.fraction

Compute membership fractions

HarveyCumulator

HarveyCumulator

holiday

Specifying Holidays

last.day.in.month

Find the last day in a month

MATCH.NumericTimestamps

Match Numeric Timestamps

match.week.to.month

Find the month containing a week

max.window.width

Maximum Window Width for a Holiday

mbsts

Multivariate Bayesian Structural Time Series

mixed.frequency

Models for mixed frequency time series

month.distance

Elapsed time in months

named.holidays

Holidays Recognized by Name

one.step.prediction.errors

Prediction Errors

plot.bsts.mixed

Plotting functions for mixed frequency Bayesian structural time series

plot.bsts.prediction

Plot predictions from Bayesian structural time series

plot.bsts.predictors

Plot the most likely predictors

plot.bsts

Plotting functions for Bayesian structural time series

plot.holiday

Plot Holiday Effects

plot.mbsts.prediction

Plot Multivariate Bsts Predictions

plot.mbsts

Plotting Functions for Multivariate Bayesian Structural Time Series

predict.bsts

Prediction for Bayesian Structural Time Series

predict.mbsts

Prediction for Multivariate Bayesian Structural Time Series

quarter

Find the quarter in which a date occurs

regression.holiday

Regression Based Holiday Models

regularize.timestamps

Produce a Regular Series of Time Stamps

residuals.bsts

Residuals from a bsts Object

shorten

Shorten long names

simulate.fake.mixed.frequency.data

Simulate fake mixed frequency data

spike.slab.ar.prior

Spike and Slab Priors for AR Processes

state.sizes

Compute state dimensions

StateSpecification

Add a state component to a Bayesian structural time series model

SuggestBurn

Suggested burn-in size

summary.bsts

Summarize a Bayesian structural time series object

to.posixt

Convert to POSIXt

week.ends

Check to see if a week contains the end of a month or quarter

weekday.names

Days of the Week

wide.to.long

Convert Between Wide and Long Format

Time series regression using dynamic linear models fit using MCMC. See Scott and Varian (2014) <DOI:10.1504/IJMMNO.2014.059942>, among many other sources.

  • Maintainer: Steven L. Scott
  • License: LGPL-2.1 | MIT + file LICENSE
  • Last published: 2024-01-17