Merge pull request #60 from palatej/develop

Improvement of CanovaHansen tests

NAMESPACE

@@ -247,6 +247,7 @@ export(sarima_model)
 export(sarima_properties)
 export(sarima_random)
 export(seasonality_canovahansen)
+export(seasonality_canovahansen_trigs)
 export(seasonality_combined)
 export(seasonality_f)
 export(seasonality_friedman)
@@ -270,7 +271,7 @@ export(statisticaltest)
 export(stock_td)
 export(tc_variable)
 export(td)
-export(td_ch)
+export(td_canovahansen)
 export(td_f)
 export(testofruns)
 export(testofupdownruns)

NEWS.md

@@ -8,6 +8,12 @@ to [Semantic Versioning](https://semver.org/spec/v3.2.3.html).
 
 ## [Unreleased]
 
+### Changed
+
+* New JARS
+* Improve Canova-Hansen tests for seasonality and trading days (new options, more output)
+* Document (UC)ARIMA models
+
 ## [3.2.4] - 2024-07-12
 
 

R/arima.R

@@ -78,7 +78,7 @@ sarima_random<-function(model, length, stde=1, tdegree=0, seed=-1){
 #' @param rmod trend threshold.
 #' @param epsphi seasonal tolerance (in degrees).
 #'
-#' @return
+#' @return An UCARIMA model
 #' @export
 #'
 #' @examples

R/tests_seasonality.R

@@ -133,19 +133,59 @@ seasonality_combined<-function(data, period, firstperiod=cycle(data)[1], mul=TRU
  evolutive=.p2r_anova(p$evolutive_seasonality)))
 }
 
-#' Seasonal Canova-Hansen test
+#' Canova-Hansen test using trigonometric variables
 #'
 #' @inheritParams seasonality_qs
-#' @param p0 Initial periodicity (included).
-#' @param p1 Final periodicity (included).
-#' @param np Number of periodicities equally spaced in \eqn{[p_0,p_1]}.
+#' @param periods Periodicities.
+#' @param lag1 Lagged variable in the regression model.
+#' @param kernel Kernel used to compute the robust covariance matrix.
+#' @param order The truncation parameter used to compute the robust covariance matrix.
 #' @param original `TRUE` for original algorithm, `FALSE` for solution proposed by T. Proietti (based on Ox code).
 #'
 #' @export
 #'
 #' @examples
-seasonality_canovahansen<-function(data, p0, p1, np, original=FALSE){
- jtest<-.jcall("jdplus/sa/base/r/SeasonalityTests", "[D", "canovaHansenTest",
- as.numeric(data), as.numeric(p0), as.numeric(p1), as.integer(np), as.logical(original))
- return(jtest)
+#' s<-log(ABS$X0.2.20.10.M)
+#' freqs<-seq(0.01, 0.5, 0.001)
+#' plot(seasonality_canovahansen_trigs(s, 1/freqs, original = FALSE), type='l')
+seasonality_canovahansen_trigs<-function(data, periods, lag1=TRUE,
+ kernel=c("Bartlett", "Square", "Welch", "Tukey", "Hamming", "Parzen"),
+ order=NA, original=FALSE){
+
+ kernel<-match.arg(kernel)
+ if (is.na(order)) order<--1
+
+ jtest<-.jcall("jdplus/sa/base/r/SeasonalityTests", "[D", "canovaHansenTrigs",
+ as.numeric(data), .jarray(periods),
+ as.logical(lag1), kernel, as.integer(order), as.logical(original))
+ return(jtest)
+}
+
+#' Canova-Hansen seasonality test
+#'
+#' @inheritParams seasonality_qs
+#' @param trigs TRUE for trigonometric variables, FALSE for seasonal dummies.
+#' @param lag1 Lagged variable in the regression model.
+#' @param kernel Kernel used to compute the robust covariance matrix.
+#' @param order The truncation parameter used to compute the robust covariance matrix.
+#' @param start Position of the first observation of the series
+#' @return list with the joint test and with details for the different seasonal variables
+#' @export
+#'
+#' @examples
+#' s<-log(ABS$X0.2.20.10.M)
+#' seasonality_canovahansen(s, 12, trigs = FALSE)
+#' seasonality_canovahansen(s, 12, trigs = TRUE)
+seasonality_canovahansen<-function(data, period, trigs=TRUE, lag1=TRUE,
+ kernel=c("Bartlett", "Square", "Welch", "Tukey", "Hamming", "Parzen"),
+ order=NA, start=1){
+ kernel<-match.arg(kernel)
+ if (is.na(order)) order<--1
+
+ q<-.jcall("jdplus/sa/base/r/SeasonalityTests", "[D", "canovaHansen",
+ as.numeric(data), as.integer(period),
+ as.logical(trigs), as.logical(lag1),
+ kernel, as.integer(order), as.integer(start-1))
+ last<-length(q)
+ return(list(joint=q[last], details=q[-last]))
 }

R/tests_td.R

@@ -54,17 +54,27 @@ td_f<-function(s, model=c("D1", "DY", "DYD1", "WN", "AIRLINE", "R011", "R100"),
  return(.jd2r_test(jtest))
 }
 
-#' Canova-Hansen Trading Days test
+#' Canova-Hansen test for stable trading days
 #'
 #' @inheritParams td_f
-#' @param differencing differencing lags.
+#' @param differencing Differencing lags.
+#' @param kernel Kernel used to compute the robust covariance matrix.
+#' @param order The truncation parameter used to compute the robust covariance matrix.
 #'
-#' @return
+#' @return list with the joint test and with details for the different days (starting with Mondays).
 #' @export
 #'
 #' @examples
-td_ch<-function(s, differencing){
- jts<-.r2jd_tsdata(s)
- return(.jcall("jdplus/toolkit/base/r/modelling/TradingDaysTests", "[D", "chTest",
- jts, .jarray(as.integer(differencing))))
+#' s<-log(ABS$X0.2.20.10.M)
+#' td_canovahansen(s, c(1,12))
+td_canovahansen<-function(s, differencing, kernel=c("Bartlett", "Square", "Welch", "Tukey", "Hamming", "Parzen"),
+ order=NA){
+ kernel<-match.arg(kernel)
+ if (is.na(order)) order<--1
+ jts<-.r2jd_tsdata(s)
+ q<-.jcall("jdplus/toolkit/base/r/modelling/TradingDaysTests", "[D", "canovaHansen",
+ jts, .jarray(as.integer(differencing)), kernel, as.integer(order))
+
+ last<-length(q)
+ return(list(joint=q[last], details=q[-last]))
 }