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).