News update

Author: Alowis

.Rbuildignore

@@ -7,3 +7,4 @@
 ^cran-comments\.md$
 ^CRAN-SUBMISSION$
 ^LICENSE\.md$
+^revdep$

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: RtsEva
 Title: Performs the Transformed-Stationary Extreme Values Analysis 
-Version: 1.0.0
+Version: 1.1.0
 Authors@R: 
     person(given = "Alois",
            family = "Tilloy",

NEWS.md

@@ -1,3 +1,32 @@
-# RtsEva 1.0.0
+# News
 
-* Added a `NEWS.md` file to track changes to the package.
+All notable changes to this project will be documented in this file.
+
+## [RtsEva 1.1.0] - 2025-06-09
+
+### Added
+
+* 'tsEvaTransformSeriesToStationaryMMXTrend()' added. It computes the trend of
+monthly maxima and adds to the suite of trend computation functions.
+
+
+### Changed
+
+* New rules for the selection of the optimal GPD fit in 'tsGetPOT'. The fit is 
+now constrained based on the shape parameter value (need to be between two bounds)
+and the AIC. 
+* TrendTH can be specified outside the 'TsEvaNs' function
+* Shape bounds updated in 'TsEvaNs'
+* Updated handling of trendPeaks cases in 'TsEvaNs': increase robustness with 
+iterative approach in cases where the trend is completely stable. 
+* 'check_timeseries' now accepts timeseries where a maximum of two years are missing
+
+
+### Fixed
+
+* Correction of a mistake in the output writing of 'tsEvaComputeReturnLevelsGEV'. 
+The output matrix was not initiated properly. The new matrix is a transposition 
+the old one.
+
+
+## [1.0.0] - 2024-06-24

R/trend_functions.R

@@ -1621,11 +1621,11 @@ tsEvaDetrendTimeSeries <- function(timeStamps, series, timeWindow, percent = NA,
 #'cat("computing trend seasonality ...\n")
 #'seasonalitySeries <- rs@detrendSeries
 #'result <- tsEstimateAverageSeasonality(timeStamps, seasonalitySeries, timeWindow=rs@nRunMn)
-#'plot(result$regime, type = "l", xlab = "Day", ylab = "Regime", main = "Estimated Regime")
-#'plot(result$Seasonality$averageSeasonalitySeries, type = "l", xlab = "Day",
-#'ylab = "Seasonality", main = "Average Seasonality")
-#'plot(result$Seasonality$varyingSeasonalitySeries, type = "l", xlab = "Day",
-#'ylab = "Seasonality", main = "Varying Seasonality")
+#'#plot(result$regime, type = "l", xlab = "Day", ylab = "Regime", main = "Estimated Regime")
+#'#plot(result$Seasonality$averageSeasonalitySeries, type = "l", xlab = "Day",
+#'#ylab = "Seasonality", main = "Average Seasonality")
+#'#plot(result$Seasonality$varyingSeasonalitySeries, type = "l", xlab = "Day",
+#'#ylab = "Seasonality", main = "Varying Seasonality")
 #'@importFrom pracma interp1
 #' @export
 tsEstimateAverageSeasonality <- function(timeStamps, seasonalitySeries, timeWindow) {

README.Rmd

@@ -17,7 +17,7 @@ knitr::opts_chunk$set(
 
 <!-- badges: start -->
 [![R-CMD-check](https://github.com/Alowis/RtsEva/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/Alowis/RtsEva/actions/workflows/R-CMD-check.yaml)
-[![PRsWelcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)](https://makeapullrequest.com/)
+[![PRsWelcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)]
 [![CRAN\_Status\_Badge](http://www.r-pkg.org/badges/version/RtsEva)](https://cran.r-project.org/package=RtsEva)
 ![](https://cranlogs.r-pkg.org/badges/grand-total/RtsEva)
 <!-- badges: end -->

README.md

@@ -6,7 +6,7 @@
 <!-- badges: start -->
 
 [![R-CMD-check](https://github.com/Alowis/RtsEva/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/Alowis/RtsEva/actions/workflows/R-CMD-check.yaml)
-[![PRsWelcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)](https://makeapullrequest.com/)
+\[![PRsWelcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)\]
 [![CRAN_Status_Badge](http://www.r-pkg.org/badges/version/RtsEva)](https://cran.r-project.org/package=RtsEva)
 ![](https://cranlogs.r-pkg.org/badges/grand-total/RtsEva)
 <!-- badges: end -->
@@ -86,10 +86,6 @@ for flood and drought analysis is available here:
 A shiny app allowing the user to select different input timeseries and
 parameters: <https://alowis.shinyapps.io/RtsEva_demo/>
 
-## More
-
-https://alowis.quarto.pub/rtseva-package-demo/
-
 ## Contact
 
 For any questions or inquiries, please contact the package maintainer at