`rjd3sts`

Installation

Running rjd3 packages requires Java 17 or higher. How to set up such a configuration in R is explained here

Latest release

To get the current stable version (from the latest release):

From GitHub:

# install.packages("remotes")
remotes::install_github("rjdverse/rjd3toolkit@*release")
remotes::install_github("rjdverse/rjd3sts@*release")

From r-universe:

install.packages("rjd3sts", repos = c("https://rjdverse.r-universe.dev", "https://cloud.r-project.org"))

Development version

You can install the development version of rjd3sts from GitHub with:

# install.packages("remotes")
remotes::install_github("rjdverse/rjd3sts")

Usage

library("rjd3sts")
#> 
#> Attaching package: 'rjd3sts'
#> The following objects are masked from 'package:stats':
#> 
#>     ar, arima, cycle

y <- log(rjd3toolkit::ABS$X0.2.09.10.M)
days<-c(1,1,1,1,2,3,0)

model<-rjd3sts::model()
sarima<-rjd3sts::sarima('arima', 12, orders=c(0,1,1), seasonal=c(0,1,1))
td<-rjd3sts::reg_td('td', 12, start(y), length(y), variance=1, fixed=FALSE)

rjd3sts::add(model, sarima)
rjd3sts::add(model, td)

rslt<-rjd3sts::estimate(model, y)
cmp<-rjd3sts::smoothed_components(rslt)
ss<-rjd3sts::smoothed_states(rslt)

plot(cmp[,2], type='l', ylim=c(-0.05, 0.04), col='blue', main="Time-varying td effect (+ Sundays coeff.)", xlab="", ylab="td effect")
lines(-rowSums(ss[,15:20]), col='green', lwd = 3)

Package Maintenance and contributing

Any contribution is welcome and should be done through pull requests and/or issues. pull requests should include updated tests and updated documentation. If functionality is changed, docstrings should be added or updated.

Licensing

The code of this project is licensed under the European Union Public Licence (EUPL).

rjdverse / rjd3sts