Merge branch 'develop'

.Rbuildignore

@@ -1,19 +1,27 @@
-^appveyor\.yml$
-^docs$
-^_pkgdown\.yml$
 ^.*\.Rproj$
 ^\.Rproj\.user$
-^.lintr$
-^README.Rmd$
+
+^\.git$
+^\.github$
+
+^README\.Rmd$
 ^README-.*\.png$
-.travis.yml
-^pkgdown$
+
+^Meta$
+^docs$
 ^doc$
+^pkgdown$
+^_pkgdown\.yml$
+
+^\.lintr$
+
+^appveyor\.yml$
+.travis.yml
+
 cran-comments.md
-TODO.R
+
+^\.DS_Store$
+
 ^revdep$
-workspace
-workspace.xml
-R/test_X11.R
-^\.github$
-^LICENSE$
+^reconf\.sh$
+^pom\.xml$

.github/workflows/test-coverage.yaml

@@ -1,10 +1,7 @@
 # Workflow derived from https://github.com/r-lib/actions/tree/v2/examples
 # Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help
 on:
-  push:
-    branches: [main, develop]
-  pull_request:
-    branches: [main, develop]
+  workflow_dispatch
 
 name: test-coverage
 

.gitignore

@@ -1,9 +1,58 @@
-.Rproj.user
+# History files
 .Rhistory
+.Rapp.history
+
+# Session Data files
 .RData
+.RDataTmp
+
+# User-specific files
 .Ruserdata
+
+# Example code in package build process
+*-Ex.R
+
+# Output files from R CMD build
+/*.tar.gz
+
+# Output files from R CMD check
+/*.Rcheck/
+
+# RStudio files
+.Rproj.user/
+
+# produced vignettes
+vignettes/*.html
+vignettes/*.pdf
+Meta/
+inst/doc/
+doc/
+
+# OAuth2 token, see https://github.com/hadley/httr/releases/tag/v0.3
+.httr-oauth
+
+# knitr and R markdown default cache directories
+*_cache/
+/cache/
+
+# Temporary files created by R markdown
+*.utf8.md
+*.knit.md
+
+# R Environment Variables
+.Renviron
+
+# pkgdown site
+docs/
+
+# translation temp files
+po/*~
+
+# RStudio Connect folder
+rsconnect/
+
+# Hidden file from mac-os
 .DS_Store
-workspace
-workspace.xml
-inst/doc
-docs
+
+# produced README.html
+README.html

DESCRIPTION

@@ -1,39 +1,41 @@
 Package: rjd3filters
 Type: Package
-Title: Trend-Cycle Extraction with Linear Filters
-Version: 2.1.0
+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", "cre"),
-                email = "[email protected]"),
-  person("Alain", "Quartier-la-Tente", role = c("aut"),
+  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"))
-                )
+                 comment = c(ORCID = "0000-0001-7890-3857")),
+  person("Tanguy", "Barthelemy", role = c("ctb", "art"),
+                 email ="[email protected]"),
+  person("Anna", "Smyk", role = c("ctb"),
+                 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,
   MASS,
   graphics,
   stats,
   rjd3toolkit (>= 3.2.2)
-Remotes:
-  github::rjdemetra/rjd3toolkit
+Remotes: 
+    github::rjdverse/rjd3toolkit@*release
 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

NAMESPACE

@@ -38,7 +38,11 @@ S3method(sum,moving_average)
 S3method(to_seasonal,default)
 S3method(to_seasonal,finite_filters)
 export(.jd2r_finitefilters)
+export(confint_filter)
+export(cp)
 export(cross_validation)
+export(cv)
+export(cve)
 export(dfa_filter)
 export(diagnostic_matrix)
 export(filter)
@@ -50,9 +54,11 @@ export(get_moving_average)
 export(get_properties_function)
 export(implicit_forecast)
 export(impute_last_obs)
+export(is.finite_filters)
 export(is.moving_average)
 export(is_symmetric)
 export(localpolynomials)
+export(loocve)
 export(lower_bound)
 export(lp_filter)
 export(mirror)
@@ -65,6 +71,7 @@ export(rkhs_filter)
 export(rkhs_kernel)
 export(rkhs_optimal_bw)
 export(rkhs_optimization_fun)
+export(rt)
 export(simple_ma)
 export(to_seasonal)
 export(upper_bound)
@@ -91,8 +98,11 @@ importFrom(rjd3toolkit,.r2jd_matrix)
 importFrom(stats,coef)
 importFrom(stats,coefficients)
 importFrom(stats,deltat)
+importFrom(stats,end)
 importFrom(stats,frequency)
 importFrom(stats,is.ts)
+importFrom(stats,qnorm)
 importFrom(stats,start)
 importFrom(stats,time)
 importFrom(stats,ts)
+importFrom(stats,ts.union)

NEWS.md

@@ -7,6 +7,23 @@ to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
 ## [Unreleased]
 
+## [2.1.1] - 2024-07-12
+
+
+### Changed
+
+* `cross_validation()` function renamed to `cve()`, `cross_validation()` is now deprecated.
+* New .jar files added (related to [v2.2.0](https://github.com/jdemetra/jdplus-incubator/releases/tag/v2.2.0))
+
+### Added
+
+* New functions to compute functions to compute diagnostics and goodness of fit of filtered series: cross validation (`cv()`) and cross validate estimate (`cve()`), leave-one-out cross validation estimate (`loocve`), CP statistic (`cp()`) and Rice's T statistics (`rt()`).
+
+* New function `confint_filter()` to compute confidence intervals for filtered series.
+
+* New function `is.finite_filters()`.
+
+* New parameter `zero_as_na` in `cbind.moving_average`, boolean indicating if trealing and leading zeros added to have a matrix form should be replaced by `NA`.
 
 ## [2.0.0] - 2023-12-12
 
@@ -23,6 +40,7 @@ to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 * New Jars
 
 
-[Unreleased]: https://github.com/rjdemetra/rjd3filters/compare/v2.0.0...HEAD
-[2.0.0]: https://github.com/rjdemetra/rjd3filters/releases/tag/v1.0.0...v2.0.0
-[1.0.0]: https://github.com/rjdemetra/rjd3filters/releases/tag/v1.0.0
+[Unreleased]: https://github.com/rjdverse/rjd3filters/compare/v2.1.1...HEAD
+[2.1.1]: https://github.com/rjdverse/rjd3filters/releases/tag/v2.0.0...v2.1.1
+[2.0.0]: https://github.com/rjdverse/rjd3filters/releases/tag/v1.0.0...v2.0.0
+[1.0.0]: https://github.com/rjdverse/rjd3filters/releases/tag/v1.0.0

R/1_moving_average.R

@@ -13,6 +13,9 @@ setClass("moving_average",
 #' @param i,j,value indices specifying elements to extract or replace and the new value
 #'
 #' @param ...,drop,na.rm other parameters.
+#' @param zero_as_na boolean indicating if, when merging several moving averages (`cbind`)
+#' if trealing and leading zeros added to have a matrix form should be replaced by `NA`.
+#'
 #' @name filters_operations
 NULL
 
@@ -72,7 +75,7 @@ NULL
 #' @export
 moving_average <- function(x, lags = -length(x), trailing_zero = FALSE, leading_zero = FALSE){
   if (inherits(x, "moving_average"))
-    return (x)
+    return(x)
   x <- as.numeric(x)
   if (trailing_zero)
     x <- rm_trailing_zero_or_na(x)
@@ -113,7 +116,7 @@ moving_average <- function(x, lags = -length(x), trailing_zero = FALSE, leading_
 is.moving_average <- function(x){
   is(x, "moving_average")
 }
-#' @importFrom stats coef coefficients
+#' @importFrom stats coef coefficients end qnorm ts.union
 #' @export
 coef.moving_average <- function(object, ...){
   coefs <- object@coefficients
@@ -190,7 +193,7 @@ setMethod("[",
             indices <- seq_along(coefs)[i]
             coefs[-indices] <- 0
             if (all(coefs == 0))
-              return (moving_average(0, lags = lower_bound(x) + indices - 1))
+              return(moving_average(0, lags = lower_bound(x) + indices - 1))
 
             moving_average(coefs, lags = lower_bound(x),
                            leading_zero = TRUE, trailing_zero = TRUE)

R/2_finite_filters.R

@@ -12,6 +12,7 @@ setClass("finite_filters",
 #' @param first_to_last boolean indicating if the first element of `rfilters` is the
 #' first asymmetric filter (when only one observation is missing) or the last one (real-time estimates).
 #' @param object `finite_filters` object.
+#' @param x object to test the class.
 #'
 #' @examples
 #' ff_lp <- lp_filter()
@@ -33,17 +34,17 @@ finite_filters.moving_average <- function(sfilter,
                                           rfilters = NULL,
                                           lfilters = NULL,
                                           first_to_last = FALSE){
-  if (is.null(lfilters) & !is.null(rfilters)) {
+  if (is.null(lfilters) && !is.null(rfilters)) {
     if (first_to_last) {
       rfilters <- rev(rfilters)
     }
     lfilters <- rev(lapply(rfilters, rev.moving_average))
-  } else if (!is.null(lfilters) & is.null(rfilters)) {
+  } else if (!is.null(lfilters) && is.null(rfilters)) {
     if (!first_to_last) {
       lfilters <- rev(lfilters)
     }
     rfilters <- rev(lapply(lfilters, rev.moving_average))
-  } else if (is.null(lfilters) & is.null(rfilters)) {
+  } else if (is.null(lfilters) && is.null(rfilters)) {
     rfilters <- lfilters <- list()
 
   }
@@ -81,6 +82,11 @@ finite_filters.matrix <- function(sfilter,
   finite_filters(coefs, first_to_last = first_to_last)
 }
 
+#' @rdname finite_filters
+#' @export
+is.finite_filters <- function(x){
+    is(x, "finite_filters")
+}
 
 #' @export
 .jd2r_finitefilters <- function(jf, first_to_last){
@@ -100,7 +106,7 @@ finite_filters.matrix <- function(sfilter,
           rfilters <- rev(rfilters)
         }
       } else {
-        if(first_to_last) {
+        if (first_to_last) {
           lfilters <- rev(lfilters)
           rfilters <- rev(rfilters)
         }
@@ -323,7 +329,7 @@ as.matrix.finite_filters <- function(x, sfilter = TRUE, rfilters = TRUE, lfilter
   sfilter_s <- rfilters_s <- lfilters_s <-
     index_s <- index_r <- index_l <- NULL
   if (!any(sfilter, rfilters, lfilters))
-    return (NULL)
+    return(NULL)
   if (sfilter) {
     sfilter_s <- list(x@sfilter)
     index_s <- length(x@rfilters)
@@ -498,7 +504,11 @@ to_seasonal.finite_filters <- function(x, s){
 #' @details
 #' When combining finite filters and a moving average, the first and/or the last points cannot be computed.
 #'
-#' For example, using the M2X12 moving average (symmetric moving average with coefficients \eqn{\theta = \begin{pmatrix} 1/24 & 1/12 & 1/12 & 1/12 & 1/12 & 1/12 & 1/12 & 1/12 & 1/12 & 1/12 & 1/12 & 1/12 & 1/24 \end{pmatrix}}), the first and last 6 points cannot be computed.
+#' For example, using the M2X12 moving average, that is to say the symmetric moving average with coefficients
+#' \deqn{
+#' \theta = \frac{1}{24}B^{6} + \frac{1}{12}B^{5}+\dots+\frac{1}{12}B^{-5}+\frac{1}{24}B^{-6},
+#' }
+#' the first and last 6 points cannot be computed.
 #'
 #' `impute_last_obs()` allows to impute the first/last points using the `nperiod` previous filtered data. With `nperiod = 1`, the last filtered data is used for the imputation, with `nperiod = 12` and monthly data, the last year filtered data is used for the imputation, etc.
 #'

R/RKHS.R

@@ -13,12 +13,7 @@
 #' @examples
 #' rkhs <- rkhs_filter(horizon = 6, asymmetricCriterion = "Timeliness")
 #' plot_coef(rkhs)
-#' @return An object of class \code{"rkhs_filter"}, which is a list of 4 elements:\itemize{
-#' \item{\code{"internal"}}{Java object used for internal functions}
-#' \item{\code{"filters.coef"}}{The coefficients of the selected filter}
-#' \item{\code{"filters.gain"}}{The gain function between 0 and pi (601 observations)}
-#' \item{\code{"filters.phase"}}{The phase function between 0 and pi (601 observations)}
-#' }
+#' @return a [finite_filters()] object.
 #' @export
 rkhs_filter <- function(horizon = 6, degree = 2,
                         kernel = c("BiWeight", "Henderson", "Epanechnikov", "Triangular", "Uniform", "TriWeight"),