diff --git a/.Rbuildignore b/.Rbuildignore
new file mode 100644
index 0000000..931662b
--- /dev/null
+++ b/.Rbuildignore
@@ -0,0 +1,3 @@
+^.*\.Rproj$
+^\.Rproj\.user$
+^README\.Rmd$
diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000..5b6a065
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,4 @@
+.Rproj.user
+.Rhistory
+.RData
+.Ruserdata
diff --git a/DESCRIPTION b/DESCRIPTION
new file mode 100644
index 0000000..82e89e8
--- /dev/null
+++ b/DESCRIPTION
@@ -0,0 +1,34 @@
+Package: rjd3highfreq
+Type: Package
+Title: Seasonal Adjustment of High Frequency Data with 'JDemetra+ 3.0'
+Version: 1.0.0
+Authors@R: c(
+  person("Jean", "Palate", role = c("aut", "cre"),
+                email = "jean.palate@nbb.be"))
+Description: Interface around 'JDemetra+ 3.x' (<https://github.com/jdemetra/jdemetra-core>) seasonal adjustment software, STACE project.
+ It offers access to several functions around the seasonal adjustment of high frequency data time series: 
+ STL, Loess, fractional airline and extension of X-11.
+Depends:
+  R (>= 3.6.0)
+Imports:
+  rJava (>= 1.0-6),
+  RProtoBuf (>= 0.4.17),
+  rjd3toolkit (>= 3.0.1),
+  rjd3sts (>= 1.0.1),
+  checkmate,
+  methods
+SystemRequirements: Java JRE 17 or higher
+License: EUPL
+URL: https://github.com/palatej/rjd3highfreq
+LazyData: TRUE
+Suggests:
+    knitr,
+    rmarkdown
+RoxygenNote: 7.2.3
+BugReports: https://github.com/palatej/rjd3highfreq/issues
+Encoding: UTF-8
+Collate: 
+    'utils.R'
+    'jd3_fractionalairline.R'
+    'print.R'
+    'zzz.R'
diff --git a/NAMESPACE b/NAMESPACE
new file mode 100644
index 0000000..d429dff
--- /dev/null
+++ b/NAMESPACE
@@ -0,0 +1,34 @@
+# Generated by roxygen2: do not edit by hand
+
+S3method(print,JDFractionalAirlineDecomposition)
+S3method(print,JDFractionalAirlineEstimation)
+export(fractionalAirlineDecomposition)
+export(fractionalAirlineDecomposition_raw)
+export(fractionalAirlineDecomposition_ssf)
+export(fractionalAirlineEstimation)
+export(jd2r_fractionalAirlineDecomposition)
+export(jd2r_multiAirlineDecomposition)
+export(multiAirlineDecomposition)
+export(multiAirlineDecomposition_raw)
+export(multiAirlineDecomposition_ssf)
+import(rjd3sts)
+importFrom(RProtoBuf,readProtoFiles2)
+importFrom(methods,new)
+importFrom(rJava,.jarray)
+importFrom(rJava,.jcall)
+importFrom(rJava,.jcast)
+importFrom(rJava,.jcastToArray)
+importFrom(rJava,.jclass)
+importFrom(rJava,.jevalArray)
+importFrom(rJava,.jinstanceof)
+importFrom(rJava,.jnew)
+importFrom(rJava,.jnull)
+importFrom(rJava,.jpackage)
+importFrom(rJava,is.jnull)
+importFrom(rjd3toolkit,dictionary)
+importFrom(rjd3toolkit,result)
+importFrom(stats,frequency)
+importFrom(stats,is.ts)
+importFrom(stats,pt)
+importFrom(stats,start)
+importFrom(stats,ts)
diff --git a/R/jd3_fractionalairline.R b/R/jd3_fractionalairline.R
new file mode 100644
index 0000000..320f970
--- /dev/null
+++ b/R/jd3_fractionalairline.R
@@ -0,0 +1,329 @@
+#' @include utils.R
+NULL
+
+ucm_extract<-function(jrslt, cmp){
+  path<-paste0("ucarima.component(", cmp,")")
+  return (arima_extract(jrslt, path))
+}
+
+arima_extract<-function(jrslt, path){
+  str<-rjd3toolkit::.proc_str(jrslt, paste0(path, ".name"))
+  ar<-rjd3toolkit::.proc_vector(jrslt, paste0(path, ".ar"))
+  delta<-rjd3toolkit::.proc_vector(jrslt, paste0(path, ".delta"))
+  ma<-rjd3toolkit::.proc_vector(jrslt, paste0(path, ".ma"))
+  var<-rjd3toolkit::.proc_numeric(jrslt, paste0(path, ".var"))
+  return (rjd3toolkit::arima_model(str, ar,delta,ma,var))
+}
+
+
+
+#' Perform an Arima Model Based (AMB) decomposition
+#'
+#' @param y input time series.
+#' @param period period of the seasonal component, any positive real number.
+#' @param adjust Boolean: TRUE: actual fractional airline model is to be used, FALSE: the period is rounded to the nearest integer.
+#' @param sn decomposition into signal and noise (2 components only). The signal is the seasonally adjusted series and the noise the seasonal component.
+#' @param stde Boolean: TRUE: compute standard deviations of the components. In some cases (memory limits), it is currently not possible to compute them
+#' @param nbcasts number of backcasts.
+#' @param nfcasts number of forecasts.
+#'
+#' @return
+#' @export
+#'
+#' @examples
+fractionalAirlineDecomposition <- function(y, period, sn = F, stde = F, nbcasts = 0, nfcasts = 0) 
+{
+  checkmate::assertNumeric(y, null.ok = F)
+  checkmate::assertNumeric(period, len = 1, null.ok = F)
+  checkmate::assertLogical(sn, len = 1, null.ok = F)
+  jrslt <- .jcall("jdplus/highfreq/base/r/FractionalAirlineProcessor", 
+                  "Ljdplus/highfreq/base/core/extendedairline/decomposition/LightExtendedAirlineDecomposition;", 
+                  "decompose", as.numeric(y), period, sn, stde, as.integer(nbcasts), 
+                  as.integer(nfcasts))
+  return(jd2r_fractionalAirlineDecomposition(jrslt, sn, stde, period))
+}
+
+
+#' Perform an Arima Model Based (AMB) decomposition on several periodcities at once
+#'
+#' @param y input time series.
+#' @param periods vector of periods values of the seasonal component, any positive real numbers.
+#' @param adjust Boolean: TRUE: actual fractional airline model is to be used, FALSE: the period is rounded to the nearest integer.
+#' @param sn decomposition into signal and noise (2 components only). The signal is the seasonally adjusted series and the noise the seasonal component.
+#' @param stde Boolean: TRUE: compute standard deviations of the components. In some cases (memory limits), it is currently not possible to compute them
+#' @param nbcasts number of backcasts.
+#' @param nfcasts number of forecasts.
+#'
+#' @return
+#' @export
+#'
+#' @examples
+multiAirlineDecomposition <- function(y, periods, ndiff = 2, ar = F, stde = F, nbcasts = 0, 
+                                      nfcasts = 0) 
+{
+  if (length(periods) == 1) {
+    return(fractionalAirlineDecomposition(y, periods, stde = stde, 
+                                          nbcasts = nbcasts, nfcasts = nfcasts))
+  }
+  checkmate::assertNumeric(y, null.ok = F)
+  jrslt <- .jcall("jdplus/highfreq/base/r/FractionalAirlineProcessor", 
+                  "Ljdplus/highfreq/base/core/extendedairline/decomposition/LightExtendedAirlineDecomposition;", 
+                  "decompose", as.numeric(y), .jarray(periods), as.integer(ndiff), 
+                  ar, stde, as.integer(nbcasts), as.integer(nfcasts))
+  if (length(periods) == 1) {
+    return(jd2r_fractionalAirlineDecomposition(jrslt, F, 
+                                               stde, periods))
+  }
+  else {
+    return(jd2r_multiAirlineDecomposition(jrslt, stde, periods))
+  }
+}
+
+
+#' Linearize the series with a fractional airline model
+#'
+#' @param y input time series.
+#' @param periods vector of periods values of the seasonal component, any positive real numbers.
+#' @param x matrix of user-defined regression variables (see rjd3toolkit for building calendar regressors).
+#' @param mean add constant mean to y after differencing.
+#' @param outliers type of outliers sub vector of c("AO","LS","WO")
+#' @param criticalValue Critical value for automatic outlier detection
+#' @param precision Precision of the likelihood 
+#' @param approximateHessian Compute approximate hessian (based on the optimizing procedure)
+#' @param nfcasts Number of forecasts
+#'
+#' @return
+#' @export
+#'
+#' @examples
+fractionalAirlineEstimation <- function(
+    y, periods, x = NULL, ndiff = 2, ar = F, mean = FALSE, 
+    outliers = NULL, criticalValue = 6, precision = 1e-12, approximateHessian = F, nfcasts=0) 
+{
+  checkmate::assertNumeric(y, null.ok = F)
+  checkmate::assertNumeric(criticalValue, len = 1, null.ok = F)
+  checkmate::assertNumeric(precision, len = 1, null.ok = F)
+  checkmate::assertLogical(mean, len = 1, null.ok = F)
+  if (is.null(outliers)) 
+    joutliers <- .jnull("[Ljava/lang/String;")
+  else joutliers = .jarray(outliers, "java.lang.String")
+  jrslt <- .jcall("jdplus/highfreq/base/r/FractionalAirlineProcessor", 
+                  "Ljdplus/highfreq/base/core/extendedairline/ExtendedAirlineEstimation;", "estimate", 
+                  as.numeric(y), rjd3toolkit::.r2jd_matrix(x), mean, .jarray(periods), 
+                  as.integer(ndiff), ar, joutliers, criticalValue, precision, 
+                  approximateHessian, as.integer(nfcasts))
+  model <- list(
+    y = as.numeric(y), 
+    periods = periods, 
+    variables = rjd3toolkit::.proc_vector(jrslt, "variables"), 
+    xreg = rjd3toolkit::.proc_matrix(jrslt, "regressors"), 
+    b = rjd3toolkit::.proc_vector(jrslt, "b"), 
+    bcov = rjd3toolkit::.proc_matrix(jrslt, "bvar"), 
+    linearized = rjd3toolkit::.proc_vector(jrslt, "lin"), 
+    component_wo = rjd3toolkit::.proc_vector(jrslt, "component_wo"), 
+    component_ao = rjd3toolkit::.proc_vector(jrslt, "component_ao"), 
+    component_ls = rjd3toolkit::.proc_vector(jrslt, "component_ls"), 
+    component_outliers = rjd3toolkit::.proc_vector(jrslt, "component_outliers"), 
+    component_userdef_reg_variables = rjd3toolkit::.proc_vector(jrslt, "component_userdef_reg_variables"), 
+    component_mean = rjd3toolkit::.proc_vector(jrslt, "component_mean"))
+  
+  estimation <- list(parameters = rjd3toolkit::.proc_vector(jrslt, "parameters"), 
+                     score = rjd3toolkit::.proc_vector(jrslt, "score"), 
+                     covariance = rjd3toolkit::.proc_matrix(jrslt, "pcov"))
+  
+  likelihood <- rjd3toolkit::.proc_likelihood(jrslt, "likelihood.")
+  
+  return(structure(list(model = model, 
+                        estimation = estimation, 
+                        likelihood = likelihood), 
+                   class = "JDFractionalAirlineEstimation"))
+}
+
+#' Title
+#'
+#' @param y 
+#' @param periods 
+#' @param ndiff 
+#' @param stde 
+#' @param nbcasts 
+#' @param nfcasts 
+#'
+#' @return
+#' @export
+#'
+#' @examples
+multiAirlineDecomposition_raw<-function(y, periods, ndiff=2, ar=F, stde=F, nbcasts=0, nfcasts=0){
+  checkmate::assertNumeric(y, null.ok = F)
+  
+  jrslt<-.jcall("jdplus/highfreq/base/r/FractionalAirlineProcessor", 
+                "Ljdplus/highfreq/base/core/extendedairline/decomposition/LightExtendedAirlineDecomposition;", 
+                "decompose", as.numeric(y), 
+                .jarray(periods), as.integer(ndiff), ar, stde, as.integer(nbcasts), as.integer(nfcasts))
+  
+  return (jrslt)
+}
+
+#' Title
+#'
+#' @param jdecomp 
+#'
+#' @return
+#' @export
+#'
+#' @examples
+multiAirlineDecomposition_ssf<-function(jdecomp){
+  jssf<-.jcall("jdplus/highfreq/base/r/FractionalAirlineProcessor", 
+               "Ljdplus/highfreq/base/core/ssf/extractors/SsfUcarimaEstimation;", "ssfDetails", jdecomp)
+  return (rjd3toolkit::.jd3_object(jssf, result=T))
+}
+
+#' Title
+#'
+#' @param y 
+#' @param period 
+#' @param sn 
+#' @param stde 
+#' @param nbcasts 
+#' @param nfcasts 
+#'
+#' @return
+#' @export
+#'
+#' @examples
+fractionalAirlineDecomposition_raw<-function(y, period, sn=F, stde=F, nbcasts=0, nfcasts=0){
+  checkmate::assertNumeric(y, null.ok = F)
+  checkmate::assertNumeric(period, len = 1, null.ok = F)
+  checkmate::assertLogical(sn, len = 1, null.ok = F)
+  jrslt<-.jcall("jdplus/highfreq/base/r/FractionalAirlineProcessor", 
+                "Ljdplus/highfreq/base/core/extendedairline/decomposition/LightExtendedAirlineDecomposition;", 
+                "decompose", as.numeric(y), 
+                period, sn, stde, as.integer(nbcasts), as.integer(nfcasts))
+  return (jrslt)
+}
+
+#' Title
+#'
+#' @param jdecomp 
+#'
+#' @return
+#' @export
+#'
+#' @examples
+fractionalAirlineDecomposition_ssf<-function(jdecomp){
+  jssf<-.jcall("jdplus/highfreq/base/r/FractionalAirlineProcessor", "Ljdplus/highfreq/base/core/ssf/extractors/SsfUcarimaEstimation;", "ssfDetails", jdecomp)
+  return (rjd3toolkit::.jd3_object(jssf, result=T))
+}
+
+
+#' Title
+#'
+#' @param jrslt 
+#' @param stde 
+#'
+#' @return
+#' @export
+#'
+#' @examples
+jd2r_multiAirlineDecomposition <- function (jrslt, stde = F, periods) 
+{
+  ncmps <- rjd3toolkit::.proc_int(jrslt, "ucarima.size")
+  model <- rjd3highfreq:::arima_extract(jrslt, "ucarima_model")
+  cmps <- lapply(1:ncmps, function(cmp) {
+    return(rjd3highfreq:::ucm_extract(jrslt, cmp))
+  })
+  ucarima <- rjd3toolkit::ucarima_model(model, cmps)
+  yc <- rjd3toolkit::.proc_vector(jrslt, "y")
+  estimation <- list(
+    parameters = rjd3toolkit::.proc_vector(jrslt, "parameters"), 
+    score = rjd3toolkit::.proc_vector(jrslt, "score"), 
+    covariance = rjd3toolkit::.proc_matrix(jrslt, "pcov"), 
+    periods = periods)
+  likelihood <- rjd3toolkit::.proc_likelihood(jrslt, "likelihood.")
+  ncmps <- rjd3toolkit::.proc_int(jrslt, "ncmps")
+  if (stde) {
+    decomposition <- lapply((1:ncmps), function(j) {
+      return(cbind(
+        rjd3toolkit::.proc_vector(jrslt, paste0("cmp(", j, ")")), 
+        rjd3toolkit::.proc_vector(jrslt, paste0("cmp_stde(", j, ")"))))
+    })
+  }
+  else {
+    decomposition <- lapply((1:ncmps), function(j) {
+      return(rjd3toolkit::.proc_vector(jrslt, paste0("cmp(", j, ")")))
+    })
+  }
+  return(structure(list(ucarima = ucarima, 
+                        decomposition = decomposition, 
+                        estimation = estimation, 
+                        likelihood = likelihood), 
+                   class = "JDFractionalAirlineDecomposition"))
+}
+
+
+#' Title
+#'
+#' @param jrslt 
+#' @param sn 
+#' @param stde 
+#'
+#' @return
+#' @export
+#'
+#' @examples
+jd2r_fractionalAirlineDecomposition <- function (jrslt, sn = F, stde = F, period) 
+{
+  ncmps <- rjd3toolkit::.proc_int(jrslt, "ucarima.size")
+  model <- rjd3highfreq:::arima_extract(jrslt, "ucarima_model")
+  cmps <- lapply(1:ncmps, function(cmp) {
+    return(rjd3highfreq:::ucm_extract(jrslt, cmp))
+  })
+  ucarima <- rjd3toolkit::ucarima_model(model, cmps)
+  yc <- rjd3toolkit::.proc_vector(jrslt, "y")
+  sa <- rjd3toolkit::.proc_vector(jrslt, "sa")
+  s <- rjd3toolkit::.proc_vector(jrslt, "s")
+  if (sn) {
+    if (stde) {
+      decomposition <- list(
+        y = yc, 
+        sa = sa, 
+        s = s, 
+        s.stde = rjd3toolkit::.proc_vector(jrslt, "s_stde"))
+    }
+    else {
+      decomposition <- list(y = yc, sa = sa, s = s)
+    }
+  }
+  else {
+    t <- rjd3toolkit::.proc_vector(jrslt, "t")
+    i <- rjd3toolkit::.proc_vector(jrslt, "i")
+    if (stde) {
+      decomposition <- list(
+        y = yc, 
+        t = t, 
+        sa = sa, 
+        s = s, 
+        i = i, 
+        t.stde = rjd3toolkit::.proc_vector(jrslt, "t_stde"), 
+        s.stde = rjd3toolkit::.proc_vector(jrslt, "s_stde"), 
+        i.stde = rjd3toolkit::.proc_vector(jrslt, "i_stde"))
+    }
+    else {
+      decomposition <- list(y = yc, t = t, sa = sa, s = s, i = i)
+    }
+  }
+  estimation <- list(
+    parameters = rjd3toolkit::.proc_vector(jrslt, "parameters"), 
+    score = rjd3toolkit::.proc_vector(jrslt, "score"), 
+    covariance = rjd3toolkit::.proc_matrix(jrslt, "pcov"), 
+    periods = period)
+  
+  likelihood <- rjd3toolkit::.proc_likelihood(jrslt, "likelihood.")
+  
+  return(structure(list(ucarima = ucarima, 
+                        decomposition = decomposition, 
+                        estimation = estimation, 
+                        likelihood = likelihood), 
+                   class = "JDFractionalAirlineDecomposition"))
+}
+
+
diff --git a/R/print.R b/R/print.R
new file mode 100644
index 0000000..4926498
--- /dev/null
+++ b/R/print.R
@@ -0,0 +1,137 @@
+
+#' @export
+print.JDFractionalAirlineDecomposition <- function(x, digits = max(3L, getOption("digits") - 3L), ...)
+{
+  # Estimated MA parameters (coefs, se, student)
+  nb_freq <- length(x$estimation$parameters) - 1L
+  est_ma_params <- data.frame(
+    MA_parameter = c("Theta(1)", 
+                     paste0("Theta(", paste0("period = ", 
+                                             x$estimation$periods), ")")), 
+    Coef = x$estimation$parameters, 
+    Coef_SE = sqrt(diag(x$estimation$covariance)), 
+    check.names = FALSE) 
+  est_ma_params$Tstat <- est_ma_params$Coef / est_ma_params$Coef_SE
+  
+  cat("\n")
+  cat("Estimate MA parameters:")
+  cat("\n")
+  print(est_ma_params, row.names = FALSE)
+  
+  cat("\n")
+  cat("Decomposition:")
+  cat("\n")
+  decompo_table <- do.call(cbind, x$decomposition)
+  print(tail(decompo_table, n = 10))
+  cat("\n")
+  
+  cat("Number of observations:", formatC(x$likelihood$nobs, digits = digits))
+  cat("\n")
+  
+  cat("Sum of square residuals:", formatC(x$likelihood$ssq, digits = digits), 
+      "on", x$likelihood$df, "degrees of freedom", 
+      sep = " ")
+  cat("\n")
+  
+  cat("Log likelihood = ", formatC(x$likelihood$ll, digits = digits), 
+      ", \n\taic = ", formatC(x$likelihood$aic, digits = digits), 
+      ", \n\taicc = ", formatC(x$likelihood$aicc, digits = digits), 
+      ", \n\tbic(corrected for length) = ", 
+      formatC(x$likelihood$bicc, digits = digits), sep = "")
+  cat("\n")
+  
+  cat("Hannan–Quinn information criterion = ", 
+      formatC(x$likelihood$hannanquinn, digits = digits), sep = "")
+  
+  cat("\n\n")
+  
+  return(invisible(x))
+}
+
+#' @export
+print.JDFractionalAirlineEstimation <- function(x, digits = max(3L, getOption("digits") - 3L), ...) {
+  
+  nb_outliers <- sum((x$model$variables |> 
+                        substr(1L, 2L) |> 
+                        toupper()) %in% c("AO", "WO", "LS"))
+  nb_reg_cjo <- length(x$model$variables) - nb_outliers
+  
+  summary_coeff <-  data.frame(
+    "Variable" = x$model$variables, 
+    "Coef" = x$model$b, 
+    "Coef_SE" = sqrt(diag(x$model$bcov)))
+  summary_coeff$Tstat <- round(summary_coeff$Coef / summary_coeff$Coef_SE, digits)
+  summary_coeff$Coef <- round(summary_coeff$Coef, digits)
+  summary_coeff$Coef_SE <- round(summary_coeff$Coef_SE, digits)
+  
+  if (nb_outliers > 0) {
+    
+    outliers_coeff <- summary_coeff[(nb_reg_cjo + 1L):nrow(summary_coeff), ]
+    outliers <- outliers_coeff$Variable
+    
+  }
+  
+  if(nb_reg_cjo > 0) {
+    reg_cjo_coeff <- summary_coeff[1:nb_reg_cjo, ]
+    reg_cjo <- reg_cjo_coeff$Variable
+  }
+  
+  # Estimated MA parameters (coefs, se, student)
+  nb_freq <- (x$estimation$parameters |> length()) - 1L
+  est_ma_params <- data.frame(
+    MA_parameter = c("Theta(1)", 
+                     paste0("Theta(", paste0("period = ", 
+                                             x$model$periods), ")")),
+    Coef = x$estimation$parameters, 
+    Coef_SE = sqrt(diag(x$estimation$covariance)), 
+    check.names = FALSE) 
+  est_ma_params$Tstat <- est_ma_params$Coef / est_ma_params$Coef_SE
+  
+  cat("\n")
+  cat("Estimate MA parameters:")
+  cat("\n")
+  print(est_ma_params, row.names = FALSE)
+  
+  cat("\n")
+  cat("Number of calendar regressors:", nb_reg_cjo, ", Number of outliers :", nb_outliers)
+  cat("\n\n")
+  
+  if(nb_reg_cjo > 0) {
+    cat("TD regressors coefficients:")
+    cat("\n")
+    print(reg_cjo_coeff, row.names = FALSE)
+    # print(head(reg_cjo_coeff, 10), row.names = FALSE)
+    # if (nb_reg_cjo > 10) cat("...\n")
+    cat("\n")
+  }
+  
+  if(nb_outliers > 0) {
+    cat("Outliers coefficients:")
+    cat("\n")
+    print(outliers_coeff, row.names = FALSE)
+    # print(head(outliers_coeff, 10), row.names = FALSE)
+    # if (nb_outliers > 10) cat("...\n")
+    cat("\n")
+  }
+  
+  cat("Number of observations:", formatC(x$likelihood$nobs, digits = digits))
+  cat("\n")
+  
+  cat("Sum of square residuals:", formatC(x$likelihood$ssq, digits = digits), 
+      "on", x$likelihood$df, "degrees of freedom", 
+      sep = " ")
+  cat("\n")
+  
+  cat("Log likelihood = ", formatC(x$likelihood$ll, digits = digits), 
+      ", \n\taic = ", formatC(x$likelihood$aic, digits = digits), 
+      ", \n\taicc = ", formatC(x$likelihood$aicc, digits = digits), 
+      ", \n\tbic(corrected for length) = ", 
+      formatC(x$likelihood$bicc, digits = digits), sep = "")
+  cat("\n")
+  
+  cat("Hannan–Quinn information criterion = ", 
+      formatC(x$likelihood$hannanquinn, digits = digits), sep = "")
+  
+  cat("\n\n")
+  return(invisible(x))
+}
diff --git a/R/utils.R b/R/utils.R
new file mode 100644
index 0000000..d8fa7a0
--- /dev/null
+++ b/R/utils.R
@@ -0,0 +1,6 @@
+#' @importFrom rJava .jpackage .jcall .jnull .jarray .jevalArray .jcast .jcastToArray .jinstanceof is.jnull .jnew .jclass
+#' @importFrom RProtoBuf readProtoFiles2
+#' @importFrom stats frequency is.ts pt start ts
+#' @importFrom rjd3toolkit result dictionary   
+#' @importFrom methods new                       
+NULL
diff --git a/R/zzz.R b/R/zzz.R
new file mode 100644
index 0000000..4518ca3
--- /dev/null
+++ b/R/zzz.R
@@ -0,0 +1,16 @@
+#' @include utils.R
+#' @import rjd3sts
+
+.onLoad <- function(libname, pkgname) {
+  if (! requireNamespace("rjd3sts", quietly=T)) stop("Loading rjd3 libraries failed")
+
+  result <- .jpackage(pkgname, lib.loc=libname)
+  if (!result) stop("Loading java packages failed")
+
+  #proto.dir <- system.file("proto", package = pkgname)
+  #RProtoBuf::readProtoFiles2(protoPath = proto.dir)
+  
+  # reload extractors
+  .jcall("jdplus/toolkit/base/api/information/InformationExtractors", "V", "reloadExtractors")
+}
+
diff --git a/README.Rmd b/README.Rmd
new file mode 100644
index 0000000..217b3e1
--- /dev/null
+++ b/README.Rmd
@@ -0,0 +1,27 @@
+---
+output: github_document
+---
+
+<!-- README.md is generated from README.Rmd. Please edit that file -->
+
+```{r, include = FALSE}
+knitr::opts_chunk$set(
+  collapse = TRUE,
+  comment = "#>",
+  fig.path = "man/figures/README-",
+  out.width = "100%"
+)
+```
+
+# rjd3highfreq
+
+High-frequency time series
+
+## Installation
+
+```{r, eval = FALSE}
+# Install development version from GitHub
+# install.packages("remotes")
+remotes::install_github("palatej/rjd3toolkit")
+remotes::install_github("palatej/rjd3highfreq")
+```
\ No newline at end of file
diff --git a/README.md b/README.md
index 933648f..993feac 100644
--- a/README.md
+++ b/README.md
@@ -1 +1,15 @@
-# rjd3highfreq
\ No newline at end of file
+
+<!-- README.md is generated from README.Rmd. Please edit that file -->
+
+# rjd3highfreq
+
+High-frequency time series
+
+## Installation
+
+``` r
+# Install development version from GitHub
+# install.packages("remotes")
+remotes::install_github("palatej/rjd3toolkit")
+remotes::install_github("palatej/rjd3highfreq")
+```
diff --git a/inst/java/jdplus-highfreq-base-api-1.1.0-SNAPSHOT.jar b/inst/java/jdplus-highfreq-base-api-1.1.0-SNAPSHOT.jar
new file mode 100644
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diff --git a/inst/java/jdplus-highfreq-base-core-1.1.0-SNAPSHOT.jar b/inst/java/jdplus-highfreq-base-core-1.1.0-SNAPSHOT.jar
new file mode 100644
index 0000000..17df54c
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diff --git a/inst/java/jdplus-highfreq-base-r-1.1.0-SNAPSHOT.jar b/inst/java/jdplus-highfreq-base-r-1.1.0-SNAPSHOT.jar
new file mode 100644
index 0000000..eab0634
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diff --git a/man/fractionalAirlineDecomposition.Rd b/man/fractionalAirlineDecomposition.Rd
new file mode 100644
index 0000000..f193a25
--- /dev/null
+++ b/man/fractionalAirlineDecomposition.Rd
@@ -0,0 +1,33 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/jd3_fractionalairline.R
+\name{fractionalAirlineDecomposition}
+\alias{fractionalAirlineDecomposition}
+\title{Perform an Arima Model Based (AMB) decomposition}
+\usage{
+fractionalAirlineDecomposition(
+  y,
+  period,
+  sn = F,
+  stde = F,
+  nbcasts = 0,
+  nfcasts = 0
+)
+}
+\arguments{
+\item{y}{input time series.}
+
+\item{period}{period of the seasonal component, any positive real number.}
+
+\item{sn}{decomposition into signal and noise (2 components only). The signal is the seasonally adjusted series and the noise the seasonal component.}
+
+\item{stde}{Boolean: TRUE: compute standard deviations of the components. In some cases (memory limits), it is currently not possible to compute them}
+
+\item{nbcasts}{number of backcasts.}
+
+\item{nfcasts}{number of forecasts.}
+
+\item{adjust}{Boolean: TRUE: actual fractional airline model is to be used, FALSE: the period is rounded to the nearest integer.}
+}
+\description{
+Perform an Arima Model Based (AMB) decomposition
+}
diff --git a/man/fractionalAirlineDecomposition_raw.Rd b/man/fractionalAirlineDecomposition_raw.Rd
new file mode 100644
index 0000000..1c7ca70
--- /dev/null
+++ b/man/fractionalAirlineDecomposition_raw.Rd
@@ -0,0 +1,31 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/jd3_fractionalairline.R
+\name{fractionalAirlineDecomposition_raw}
+\alias{fractionalAirlineDecomposition_raw}
+\title{Title}
+\usage{
+fractionalAirlineDecomposition_raw(
+  y,
+  period,
+  sn = F,
+  stde = F,
+  nbcasts = 0,
+  nfcasts = 0
+)
+}
+\arguments{
+\item{y}{}
+
+\item{period}{}
+
+\item{sn}{}
+
+\item{stde}{}
+
+\item{nbcasts}{}
+
+\item{nfcasts}{}
+}
+\description{
+Title
+}
diff --git a/man/fractionalAirlineDecomposition_ssf.Rd b/man/fractionalAirlineDecomposition_ssf.Rd
new file mode 100644
index 0000000..de278e3
--- /dev/null
+++ b/man/fractionalAirlineDecomposition_ssf.Rd
@@ -0,0 +1,14 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/jd3_fractionalairline.R
+\name{fractionalAirlineDecomposition_ssf}
+\alias{fractionalAirlineDecomposition_ssf}
+\title{Title}
+\usage{
+fractionalAirlineDecomposition_ssf(jdecomp)
+}
+\arguments{
+\item{jdecomp}{}
+}
+\description{
+Title
+}
diff --git a/man/fractionalAirlineEstimation.Rd b/man/fractionalAirlineEstimation.Rd
new file mode 100644
index 0000000..76976d9
--- /dev/null
+++ b/man/fractionalAirlineEstimation.Rd
@@ -0,0 +1,42 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/jd3_fractionalairline.R
+\name{fractionalAirlineEstimation}
+\alias{fractionalAirlineEstimation}
+\title{Linearize the series with a fractional airline model}
+\usage{
+fractionalAirlineEstimation(
+  y,
+  periods,
+  x = NULL,
+  ndiff = 2,
+  ar = F,
+  mean = FALSE,
+  outliers = NULL,
+  criticalValue = 6,
+  precision = 1e-12,
+  approximateHessian = F,
+  nfcasts = 0
+)
+}
+\arguments{
+\item{y}{input time series.}
+
+\item{periods}{vector of periods values of the seasonal component, any positive real numbers.}
+
+\item{x}{matrix of user-defined regression variables (see rjd3toolkit for building calendar regressors).}
+
+\item{mean}{add constant mean to y after differencing.}
+
+\item{outliers}{type of outliers sub vector of c("AO","LS","WO")}
+
+\item{criticalValue}{Critical value for automatic outlier detection}
+
+\item{precision}{Precision of the likelihood}
+
+\item{approximateHessian}{Compute approximate hessian (based on the optimizing procedure)}
+
+\item{nfcasts}{Number of forecasts}
+}
+\description{
+Linearize the series with a fractional airline model
+}
diff --git a/man/jd2r_fractionalAirlineDecomposition.Rd b/man/jd2r_fractionalAirlineDecomposition.Rd
new file mode 100644
index 0000000..5b0a74d
--- /dev/null
+++ b/man/jd2r_fractionalAirlineDecomposition.Rd
@@ -0,0 +1,18 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/jd3_fractionalairline.R
+\name{jd2r_fractionalAirlineDecomposition}
+\alias{jd2r_fractionalAirlineDecomposition}
+\title{Title}
+\usage{
+jd2r_fractionalAirlineDecomposition(jrslt, sn = F, stde = F, period)
+}
+\arguments{
+\item{jrslt}{}
+
+\item{sn}{}
+
+\item{stde}{}
+}
+\description{
+Title
+}
diff --git a/man/jd2r_multiAirlineDecomposition.Rd b/man/jd2r_multiAirlineDecomposition.Rd
new file mode 100644
index 0000000..81d0305
--- /dev/null
+++ b/man/jd2r_multiAirlineDecomposition.Rd
@@ -0,0 +1,16 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/jd3_fractionalairline.R
+\name{jd2r_multiAirlineDecomposition}
+\alias{jd2r_multiAirlineDecomposition}
+\title{Title}
+\usage{
+jd2r_multiAirlineDecomposition(jrslt, stde = F, periods)
+}
+\arguments{
+\item{jrslt}{}
+
+\item{stde}{}
+}
+\description{
+Title
+}
diff --git a/man/multiAirlineDecomposition.Rd b/man/multiAirlineDecomposition.Rd
new file mode 100644
index 0000000..233ae71
--- /dev/null
+++ b/man/multiAirlineDecomposition.Rd
@@ -0,0 +1,34 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/jd3_fractionalairline.R
+\name{multiAirlineDecomposition}
+\alias{multiAirlineDecomposition}
+\title{Perform an Arima Model Based (AMB) decomposition on several periodcities at once}
+\usage{
+multiAirlineDecomposition(
+  y,
+  periods,
+  ndiff = 2,
+  ar = F,
+  stde = F,
+  nbcasts = 0,
+  nfcasts = 0
+)
+}
+\arguments{
+\item{y}{input time series.}
+
+\item{periods}{vector of periods values of the seasonal component, any positive real numbers.}
+
+\item{stde}{Boolean: TRUE: compute standard deviations of the components. In some cases (memory limits), it is currently not possible to compute them}
+
+\item{nbcasts}{number of backcasts.}
+
+\item{nfcasts}{number of forecasts.}
+
+\item{adjust}{Boolean: TRUE: actual fractional airline model is to be used, FALSE: the period is rounded to the nearest integer.}
+
+\item{sn}{decomposition into signal and noise (2 components only). The signal is the seasonally adjusted series and the noise the seasonal component.}
+}
+\description{
+Perform an Arima Model Based (AMB) decomposition on several periodcities at once
+}
diff --git a/man/multiAirlineDecomposition_raw.Rd b/man/multiAirlineDecomposition_raw.Rd
new file mode 100644
index 0000000..f35584e
--- /dev/null
+++ b/man/multiAirlineDecomposition_raw.Rd
@@ -0,0 +1,32 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/jd3_fractionalairline.R
+\name{multiAirlineDecomposition_raw}
+\alias{multiAirlineDecomposition_raw}
+\title{Title}
+\usage{
+multiAirlineDecomposition_raw(
+  y,
+  periods,
+  ndiff = 2,
+  ar = F,
+  stde = F,
+  nbcasts = 0,
+  nfcasts = 0
+)
+}
+\arguments{
+\item{y}{}
+
+\item{periods}{}
+
+\item{ndiff}{}
+
+\item{stde}{}
+
+\item{nbcasts}{}
+
+\item{nfcasts}{}
+}
+\description{
+Title
+}
diff --git a/man/multiAirlineDecomposition_ssf.Rd b/man/multiAirlineDecomposition_ssf.Rd
new file mode 100644
index 0000000..38e686f
--- /dev/null
+++ b/man/multiAirlineDecomposition_ssf.Rd
@@ -0,0 +1,14 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/jd3_fractionalairline.R
+\name{multiAirlineDecomposition_ssf}
+\alias{multiAirlineDecomposition_ssf}
+\title{Title}
+\usage{
+multiAirlineDecomposition_ssf(jdecomp)
+}
+\arguments{
+\item{jdecomp}{}
+}
+\description{
+Title
+}
diff --git a/rjd3highfreq.Rproj b/rjd3highfreq.Rproj
new file mode 100644
index 0000000..9dbf118
--- /dev/null
+++ b/rjd3highfreq.Rproj
@@ -0,0 +1,20 @@
+Version: 1.0
+
+RestoreWorkspace: Default
+SaveWorkspace: Default
+AlwaysSaveHistory: Default
+
+EnableCodeIndexing: Yes
+UseSpacesForTab: Yes
+NumSpacesForTab: 2
+Encoding: UTF-8
+
+RnwWeave: Sweave
+LaTeX: pdfLaTeX
+
+BuildType: Package
+PackageUseDevtools: Yes
+PackageInstallArgs: --no-multiarch --with-keep.source
+PackageBuildBinaryArgs: --no-multiarch
+PackageCheckArgs: --no-multiarch
+PackageRoxygenize: rd,collate,namespace