Merge pull request #25 from annasmyk/develop

descp file and readme update

DESCRIPTION

@@ -1,26 +1,28 @@
 Package: rjd3filters
 Type: Package
-Title: Trend-Cycle Extraction with Linear Filters
+Title: Trend-Cycle Extraction with Linear Filters based on JDemetra+ v3.x
 Version: 2.1.1
 Authors@R: c(
   person("Jean", "Palate", role = c("aut"),
-         email = "[email protected]"),
-  person("Alain", "Quartier-la-Tente", role = c("aut", "cre"),
-         email = "[email protected]",
-         comment = c(ORCID = "0000-0001-7890-3857"))
-         )
+                email = "[email protected]"),
+  person("Alain", "Quartier-la-Tente", role = c("aut"),
+                 email = "[email protected]",
+                 comment = c(ORCID = "0000-0001-7890-3857")),
+  person("Tanguy", "Barthelemy", role = c("aut","cre"),
+                 email ="[email protected]"),
+  person("Anna", "Smyk", role = c("aut"),
+                 email ="[email protected]")
+                 )
 Description: This package provides functions to build and apply symmetric
   and asymmetric moving averages (= linear filters) for trend-cycle extraction.
-  In particular, it implements several moderns approaches for real-time estimates
+  In particular, it implements several modern approaches for real-time estimates
   from the viewpoint of revisions and time delay in detecting turning points.
   It includes the local polynomial approach of Proietti and Luati (2008), the
   Reproducing Kernel Hilbert Space (RKHS) of Dagum and Bianconcini (2008) and
   the Fidelity-Smoothness-Timeliness approach of Grun-Rehomme, Guggemos, and Ladiray (2018).
-  It is based on Java libraries developped around 'JDemetra+' (<https://github.com/jdemetra/jdemetra-app>), 
-  the seasonal adjustment software officially recommended to the members 
-  of the European Statistical System (ESS) and the European System of Central Banks.
+  It is based on Java libraries developped in 'JDemetra+' (<https://github.com/jdemetra>), time series analysis software.
 Depends:
-  R (>= 3.6.0)
+  R (>= 4.1.0)
 Imports:
   rJava (>= 1.0-6),
   methods,
@@ -29,11 +31,11 @@ Imports:
   stats,
   rjd3toolkit (>= 3.2.2)
 Remotes:
-  github::rjdemetra/rjd3toolkit
+  github::rjdverse/rjd3toolkit
 SystemRequirements: Java (>= 17)
 License: EUPL
 LazyData: TRUE
-URL: https://github.com/rjdemetra/rjd3filters, https://rjdemetra.github.io/rjd3filters/
+URL: https://github.com/rjdverse/rjd3filters, https://rjdverse.github.io/rjd3filters/
 Suggests:
     knitr,
     rmarkdown

README.Rmd

@@ -16,7 +16,7 @@ knitr::opts_chunk$set(
 
 # rjd3filters
 
-rjd3filters is R package on linear filters for real-time trend-cycle estimates.
+rjd3filters is an R package on linear filters for real-time trend-cycle estimates.
 It allows to create symmetric and asymmetric moving averages with:
 
 - local polynomial filters, as defined by Proietti and Luati (2008);
@@ -29,24 +29,25 @@ Some quality criteria defined by Wildi and McElroy (2019) can also be computed.
 
 ## Installation
 
-rjd3filters relies on the [rJava](https://CRAN.R-project.org/package=rJava) package and running rjd3 packages requires Java 17 or higher. 
-If you have troubles with the installation, check the [installation manual of `RJDemetra`](https://github.com/jdemetra/rjdemetra/wiki/Installation-manual).
+rjd3filters relies on the [rJava](https://CRAN.R-project.org/package=rJava) package.
+
+Running rjd3 packages requires **Java 17 or higher**. How to set up such a configuration in R is explained [here](https://jdemetra-new-documentation.netlify.app/#Rconfig) 
 
 To get the current stable version (from the latest release):
 
 ```{r, eval = FALSE}
 # install.packages("remotes")
-remotes::install_github("rjdemetra/rjd3toolkit@*release")
-remotes::install_github("rjdemetra/rjd3filters@*release")
+remotes::install_github("rjdverse/rjd3toolkit@*release")
+remotes::install_github("rjdverse/rjd3filters@*release")
 ```
 
 To get the current development version from GitHub:
 
 ```{r, eval = FALSE}
 # install.packages("remotes")
 # Install development version from GitHub
-remotes::install_github("rjdemetra/rjd3toolkit")
-remotes::install_github("rjdemetra/rjd3filters")
+remotes::install_github("rjdverse/rjd3toolkit")
+remotes::install_github("rjdverse/rjd3filters")
 ```
 
 

README.md

@@ -3,7 +3,7 @@
 
 # rjd3filters
 
-rjd3filters is R package on linear filters for real-time trend-cycle
+rjd3filters is an R package on linear filters for real-time trend-cycle
 estimates. It allows to create symmetric and asymmetric moving averages
 with:
 
@@ -22,26 +22,27 @@ computed.
 ## Installation
 
 rjd3filters relies on the
-[rJava](https://CRAN.R-project.org/package=rJava) package and running
-rjd3 packages requires Java 17 or higher. If you have troubles with the
-installation, check the [installation manual of
-`RJDemetra`](https://github.com/jdemetra/rjdemetra/wiki/Installation-manual).
+[rJava](https://CRAN.R-project.org/package=rJava) package.
+
+Running rjd3 packages requires **Java 17 or higher**. How to set up such
+a configuration in R is explained
+[here](https://jdemetra-new-documentation.netlify.app/#Rconfig)
 
 To get the current stable version (from the latest release):
 
 ``` r
 # install.packages("remotes")
-remotes::install_github("rjdemetra/rjd3toolkit@*release")
-remotes::install_github("rjdemetra/rjd3filters@*release")
+remotes::install_github("rjdverse/rjd3toolkit@*release")
+remotes::install_github("rjdverse/rjd3filters@*release")
 ```
 
 To get the current development version from GitHub:
 
 ``` r
 # install.packages("remotes")
 # Install development version from GitHub
-remotes::install_github("rjdemetra/rjd3toolkit")
-remotes::install_github("rjdemetra/rjd3filters")
+remotes::install_github("rjdverse/rjd3toolkit")
+remotes::install_github("rjdverse/rjd3filters")
 ```
 
 ## Basic example