Kernel: R (R-Project)

R-package bsts in CoCalc

Bayesian Structural Time Series: Time series regression using dynamic linear models fit using MCMC.

https://cran.r-project.org/web/packages/bsts/index.html

In [1]:

require('bsts')

Loading required package: bsts
Loading required package: BoomSpikeSlab
Loading required package: Boom
Loading required package: MASS

Attaching package: ‘Boom’

The following object is masked from ‘package:stats’:

    rWishart

Loading required package: zoo

Attaching package: ‘zoo’

The following objects are masked from ‘package:base’:

    as.Date, as.Date.numeric

Loading required package: xts

In [2]:

data(AirPassengers)
y <- log(AirPassengers)
ss <- AddLocalLinearTrend(list(), y)
ss <- AddSeasonal(ss, y, nseasons = 12)
model <- bsts(y, state.specification = ss, niter = 500)
summary(model)

=-=-=-=-= Iteration 0 Sun Dec 10 13:17:07 2017 =-=-=-=-=
=-=-=-=-= Iteration 50 Sun Dec 10 13:17:08 2017 =-=-=-=-=
=-=-=-=-= Iteration 100 Sun Dec 10 13:17:09 2017 =-=-=-=-=
=-=-=-=-= Iteration 150 Sun Dec 10 13:17:10 2017 =-=-=-=-=
=-=-=-=-= Iteration 200 Sun Dec 10 13:17:11 2017 =-=-=-=-=
=-=-=-=-= Iteration 250 Sun Dec 10 13:17:12 2017 =-=-=-=-=
=-=-=-=-= Iteration 300 Sun Dec 10 13:17:13 2017 =-=-=-=-=
=-=-=-=-= Iteration 350 Sun Dec 10 13:17:14 2017 =-=-=-=-=
=-=-=-=-= Iteration 400 Sun Dec 10 13:17:15 2017 =-=-=-=-=
=-=-=-=-= Iteration 450 Sun Dec 10 13:17:16 2017 =-=-=-=-=

$residual.sd: 0.0211826284956157
$prediction.sd: 0.0561189186986301
$rsquare: 0.997697582822533
$relative.gof: 0.719501751226803

In [3]:

pred <- predict(model, horizon = 12, burn = 100)
summary(pred)

                Length Class  Mode   
mean              12   -none- numeric
median            12   -none- numeric
interval          24   -none- numeric
distribution    4800   -none- numeric
original.series  144   zoo    numeric

In [4]:

plot(pred)

In [0]: