New jars + likelihood (df)

.Rbuildignore

@@ -1,27 +1,20 @@
 ^.*\.Rproj$
 ^\.Rproj\.user$
-
-^\.git$
-^\.github$
-
-^README\.Rmd$
-^README-.*\.png$
-
-^Meta$
+^appveyor\.yml$
 ^docs$
-^doc$
-^pkgdown$
 ^_pkgdown\.yml$
-
-^\.lintr$
-
-^appveyor\.yml$
+^.*\.Rproj$
+^\.Rproj\.user$
+^README\.Rmd$
+^README-.*\.png$
 .travis.yml
-
+^pkgdown$
+^doc$
 cran-comments.md
-
-^\.DS_Store$
-
+TODO.R
+TO_DO
 ^revdep$
+^\.github$
+.DS_Store
 ^reconf\.sh$
 ^pom\.xml$

.github/workflows/test-coverage.yaml

@@ -1,7 +1,10 @@
 # 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:
-  workflow_dispatch
+  push:
+    branches: [main, develop]
+  pull_request:
+    branches: [main, develop]
 
 name: test-coverage
 

DESCRIPTION

@@ -1,42 +1,34 @@
 Package: rjd3toolkit
 Type: Package
-Title: Utility Functions around 'JDemetra+ 3.0'
+Title: Toolkit Functions Around 'JDemetra+ 3.0'
 Version: 3.2.3
 Authors@R: c(
-    person(given = "Jean", 
-           family = "Palate", role = c("aut"),
-           email = "[email protected]"),
-    person(given = "Alain", 
-           family = "Quartier-la-Tente", role = c("aut"),
-           email = "[email protected]",
-           comment = c(ORCID = "0000-0001-7890-3857")),
-    person(given = "Tanguy", 
-           family = "Barthelemy", role = c("aut","cre"),
-           email ="[email protected]"),
-    person(given = "Anna", 
-           family = "Smyk", role = c("aut"),
-           email ="[email protected]"))
-Description: R Interface to 'JDemetra+ 3.x' (<https://github.com/jdemetra>) time series analysis software.
- It provides functions allowing to model time series (create outlier regressors, user-defined calendar regressors,
- UCARIMA models...), to test the presence of trading days or seasonal effects and also
- to set specifications in pre-adjustment and benchmarking when using rjd3x13 or rjd3tramoseats.
+  person("Jean", "Palate", role = c("aut", "cre"),
+                email = "[email protected]"),
+  person("Alain", "Quartier-la-Tente", role = c("aut"),
+                 email = "[email protected]",
+                 comment = c(ORCID = "0000-0001-7890-3857")))
+Description: Interface around 'JDemetra+ 3.x' (<https://github.com/jdemetra/jdemetra-core>) seasonal adjustment software, STACE project.
+ It offers access to several functions to model time series (create outlier regressors, user-defined calendar regressors,
+ UCARIMA models...), to test the presence of trading days or seasonal effects and other tools around seasonal adjustment and 
+ to set specifications around pre-adjustment (RegARIMA/X-13 and TRAMO/TRAMO-SEATS).
 Depends:
-    R (>= 4.1.0)
+  R (>= 3.6.0)
 Imports:
-    RProtoBuf (>= 0.4.20),
-    rJava (>= 1.0-6),
-    checkmate,
-    methods
+	RProtoBuf (>= 0.4.20),
+  rJava (>= 1.0-6),
+  checkmate,
+  methods
 SystemRequirements: Java (>= 17)
 License: EUPL
-URL: https://github.com/rjdverse/rjd3toolkit, https://rjdverse.github.io/rjd3toolkit/
+URL: https://github.com/rjdemetra/rjd3toolkit, https://rjdemetra.github.io/rjd3toolkit/
 LazyData: TRUE
 Suggests:
     knitr,
     rmarkdown
 RoxygenNote: 7.3.1
 Roxygen: list(markdown = TRUE)
-BugReports: https://github.com/rjdverse/rjd3toolkit/issues
+BugReports: https://github.com/rjdemetra/rjd3toolkit/issues
 Encoding: UTF-8
 Collate: 
     'utils.R'

NEWS.md

@@ -7,11 +7,8 @@ to [Semantic Versioning](https://semver.org/spec/v3.2.3.html).
 
 ## [Unreleased]
 
-### Fixed
+[Unreleased]: https://github.com/rjdemetra/rjd3toolkit/compare/v3.2.3...HEAD
 
-- Correct SA decomposition with backcasts and forecasts (Java to R transfer) [#2](https://github.com/rjdverse/rjd3tramoseats/issues/2)
+## [3.2.3] - 2023-12-12
 
-## [3.2.2] - 2024-03-15 
-
-[Unreleased]: https://github.com/rjdverse/rjd3toolkit/compare/v3.2.2...HEAD
-[3.2.2]: https://github.com/rjdverse/rjd3toolkit/releases/tag/v3.2.2
+[3.2.3]: https://github.com/rjdemetra/rjd3toolkit/releases/tag/v3.2.3

R/calendars.R

@@ -48,7 +48,7 @@ SINGLEDAY<-'JD3_SINGLEDAY'
 }
 
 .length_ts <- function(s){
-    if (is.mts(s)){
+    if(is.mts(s)){
         nrow(s)
     }else{
         length(s)
@@ -294,7 +294,7 @@ special_day<-function(event, offset=0, weight=1, validity=NULL){
 }
 
 .group_names <- function(x, contrasts = TRUE){
-    if (!is.matrix(x))
+    if(!is.matrix(x))
         return(x)
     col_names <- seq_len(ncol(x)) - !contrasts #if !contrast then it starts from 0
     colnames(x) <- sprintf("group_%i", col_names)
@@ -734,7 +734,7 @@ national_calendar <- function(days, mean_correction=TRUE){
 #' More information on calendar correction in JDemetra+ online documentation:
 #' \url{https://jdemetra-new-documentation.netlify.app/}
 calendar_td<-function(calendar,frequency, start, length, s, groups=c(1,2,3,4,5,6,0), holiday=7, contrasts=TRUE){
-    if (! is(calendar, 'JD3_CALENDAR')) stop('Invalid calendar')
+    if(! is(calendar, 'JD3_CALENDAR')) stop('Invalid calendar')
     if (!missing(s) && is.ts(s)) {
         frequency <- stats::frequency(s)
         start <- stats::start(s)

R/display.R

@@ -62,9 +62,9 @@ print.JD3_SARIMA_ESTIMATION<-function(x, digits = max(3L, getOption("digits") -
   cat("\n")
 
   cat("\nCoefficients\n")
-  if (is.null(tables$coef_table)){
+  if(is.null(tables$coef_table)){
     cat("No SARIMA variables\n")
-  } else if (ncol(tables$coef_table) == 2){
+  } else if(ncol(tables$coef_table) == 2){
     print(tables$coef_table)
   } else{
     printCoefmat(tables$coef_table[-2], digits = digits,
@@ -95,9 +95,9 @@ print.summary.JD3_SARIMA_ESTIMATION<-function(x, digits = max(3L, getOption("dig
 
   cat("\n")
   cat("\nCoefficients\n")
-  if (is.null(x$coef_table)){
+  if(is.null(x$coef_table)){
     cat("No SARIMA variables\n")
-  } else if (ncol(x$coef_table) == 2){
+  } else if(ncol(x$coef_table) == 2){
     print(x$coef_table)
   } else{
     printCoefmat(x$coef_table[-2], digits = digits, signif.stars = signif.stars,
@@ -126,7 +126,7 @@ print.summary.JD3_SARIMA_ESTIMATION<-function(x, digits = max(3L, getOption("dig
     for(i in colnames(fr)){
       fr[,i] <- unlist(fr[,i])
     }
-    if (!is.null(cov) && !is.null(ndf)){
+    if(!is.null(cov) && !is.null(ndf)){
       fr$pvalue <- fr$t <- fr$stde <- NA
       stde<-sqrt(diag(cov))
       sel<-fr$type=='ESTIMATED'
@@ -150,7 +150,7 @@ print.summary.JD3_SARIMA_ESTIMATION<-function(x, digits = max(3L, getOption("dig
   .sarima_coef_table(x$description$arima, cov = cov, ndf = ndf, ...)
 }
 .sarima_coef_table.JD3_SARIMA_ESTIMATE <- function(x,...){
-  ndf<-x$likelihood$neffectiveobs-x$likelihood$nparams+1
+  ndf<-x$likelihood$neffectiveobs-x$likelihood$nparams
   sarima_orders <- list(p = x$orders$order[1],
                        d = x$orders$order[2],
                        q = x$orders$order[3],
@@ -247,10 +247,10 @@ print.summary.JD3_LIKELIHOOD<-function(x, ...){
 #' @rdname jd3_print
 #' @export
 print.JD3_REGARIMA_RSLTS<-function(x, digits = max(3L, getOption("digits") - 3L), ...){
-  cat("Log-transformation:",if (x$description$log) {"yes"} else {"no"},
+  cat("Log-transformation:",if(x$description$log) {"yes"} else {"no"},
       "\n", sep=" ")
 
-  ndf<-x$estimation$likelihood$neffectiveobs-x$estimation$likelihood$nparams+1
+  ndf<-x$estimation$likelihood$neffectiveobs-x$estimation$likelihood$nparams
   print(x$description$arima, cov = x$estimation$parameters$cov,
         ndf = ndf,
         digits = digits,
@@ -281,9 +281,9 @@ print.JD3_SARIMA_ESTIMATE<-function(x, digits = max(3L, getOption("digits") - 3L
   cat("\n")
 
   cat("\nCoefficients\n")
-  if (is.null(tables$coef_table)){
+  if(is.null(tables$coef_table)){
     cat("No SARIMA variables\n")
-  } else if (ncol(tables$coef_table) == 2){
+  } else if(ncol(tables$coef_table) == 2){
     print(tables$coef_table)
   } else{
     printCoefmat(tables$coef_table[-2], digits = digits,
@@ -312,7 +312,7 @@ print.JD3_SARIMA_ESTIMATE<-function(x, digits = max(3L, getOption("digits") - 3L
     stde<-sqrt(diag(q$estimation$bvar))
     sel<-xregs$type=='ESTIMATED'
     t<-xregs$value[sel]/stde
-    ndf<-q$estimation$likelihood$neffectiveobs-q$estimation$likelihood$nparams+1
+    ndf<-q$estimation$likelihood$neffectiveobs-q$estimation$likelihood$nparams
     pval<-2*pt(abs(t), ndf, lower.tail = FALSE)
     xregs$stde[sel]<-stde
     xregs$t[sel]<-t
@@ -325,7 +325,7 @@ print.JD3_SARIMA_ESTIMATE<-function(x, digits = max(3L, getOption("digits") - 3L
   }
 }
 .regarima_coef_table.JD3_SARIMA_ESTIMATE <- function(x,...){
-  ndf<-x$likelihood$neffectiveobs-x$likelihood$nparams+1
+  ndf<-x$likelihood$neffectiveobs-x$likelihood$nparams
 
   estimate <- x$b
   if (length(estimate) > 0){
@@ -343,7 +343,7 @@ print.JD3_SARIMA_ESTIMATE<-function(x, digits = max(3L, getOption("digits") - 3L
 #' @export
 summary.JD3_REGARIMA_RSLTS<-function(object, ...){
   log = object$description$log
-  ndf<-object$estimation$likelihood$neffectiveobs-object$estimation$likelihood$nparams+1
+  ndf<-object$estimation$likelihood$neffectiveobs-object$estimation$likelihood$nparams
   sarima_sum <- summary(object$description$arima, cov = object$estimation$parameters$cov,
                 ndf = ndf, ...)
   xregs = .regarima_coef_table(object, ...)
@@ -370,7 +370,7 @@ summary.JD3_SARIMA_ESTIMATE <-function(object, ...){
 #' @export
 print.summary.JD3_REGARIMA_RSLTS <- function(x,  digits = max(3L, getOption("digits") - 3L), signif.stars = getOption("show.signif.stars"), ...){
   if (!is.null(x$log))
-    cat("Log-transformation:",if (x$log) {"yes"} else {"no"},"\n",sep=" ")
+    cat("Log-transformation:",if(x$log) {"yes"} else {"no"},"\n",sep=" ")
 
   print(x$sarima, digits = digits, signif.stars = signif.stars, ...)
   cat("\n")

R/procresults.R

@@ -53,7 +53,7 @@ result<-function(object, id){
 #' @rdname dictionary
 #' @export
 user_defined <- function(object, userdefined = NULL){
-  if (is.null(userdefined)){
+  if(is.null(userdefined)){
     result <- list()
   } else{
     result <- lapply(userdefined,

R/protobuf.R

@@ -419,7 +419,7 @@ NULL
 }
 
 .regeffect<-function(map){
-  if (length(map) == 0)
+  if(length(map) == 0)
     return("Undefined")
   r<-which(sapply(map, function(z){z$key == "regeffect"}))
   if (length(r) == 0) return("Undefined")

R/regarima_generic.R

@@ -28,13 +28,10 @@ logLik.JD3_REGARIMA_RSLTS <- function(object, ...) {
       is.null(object$likelihood$ll)) {
     res <- NA
   } else{
-    res <- structure(
-        object$likelihood$ll,
-        # df already contains variance of innovations
-        # so we didn't add +1 as in stats:::logLik.Arima()
-        df = object$likelihood$nparams,
-        nall = object$likelihood$nobs,
-        nobs = object$likelihood$neffectiveobs)
+    res <- structure(object$likelihood$ll,
+                     df = object$likelihood$nparams,
+                     nall = object$likelihood$nobs,
+                     nobs = object$likelihood$neffectiveobs)
   }
   class(res) <- "logLik"
   res
@@ -59,8 +56,8 @@ df.residual.JD3_REGARIMA_RSLTS <- function(object, ...){
     return(NULL)
   if (!is.null(object$estimation)) # for sarima_estimate outputs
     object <- object$estimation
-  # Remove variance of innovations from parameters
-  object$likelihood$neffectiveobs - (object$likelihood$nparams - 1)
+
+  object$likelihood$neffectiveobs - object$likelihood$nparams
 }
 #' @export
 nobs.JD3_REGARIMA_RSLTS <- function(object, ...){

R/spec_benchmarking.R

@@ -15,12 +15,12 @@
 #' @param forecast Boolean indicating if the forecasts of the seasonally adjusted series and of the target variable (\code{target}) are used in the benchmarking computation so that the benchmarking constrain is also applied to the forecasting period.
 #' @param bias TODO
 #' @details
-#' \code{x} specification param must be a JD3_X13_SPEC" class object generated with \code{rjd3x13::x13_spec()}
+#' \code{x} specification param must be a JD3_X13_SPEC" class object generated with \code{rjd3x13::spec_x13()}
 #' (or "JD3_REGARIMA_SPEC" generated with \code{rjd3x13::spec_regarima()} or "JD3_TRAMOSEATS_SPEC"
 #' generated with \code{rjd3tramoseats::spec_tramoseats()} or "JD3_TRAMO_SPEC" generated with
 #' \code{rjd3tramoseats::spec_tramo()}).
 #' @examples
-#' # init_spec <- rjd3x13::x13_spec("RSA5c")
+#' # init_spec <- rjd3x13::spec_x13("RSA5c")
 #' # new_spec<- set_benchmarking(init_spec,
 #' #                            enabled = TRUE,
 #' #                            target = "Normal",