Remove UTF-8 characters in data (ASCII only).

R/datasets.R

@@ -122,7 +122,7 @@ NULL
 #' Absolute magnitude of 373 geomagnetic storms lasting more than 48h with absolute magnitude (dst) larger than 100 in 1957-2014.
 #'
 #' @source Aki Vehtari
-#' @references World Data Center for Geomagnetism, Kyoto, M. Nose, T. Iyemori, M. Sugiura, T. Kamei (2015), \emph{Geomagnetic Dst index}, doi:10.17593/14515-74000.
+#' @references World Data Center for Geomagnetism, Kyoto, M. Nose, T. Iyemori, M. Sugiura, T. Kamei (2015), \emph{Geomagnetic Dst index}, <doi:10.17593/14515-74000>.
 #' @docType data
 #' @note For a detailed article presenting the derivation of the Dst index, see \code{http://wdc.kugi.kyoto-u.ac.jp/dstdir/dst2/onDstindex.html}
 #' @format a vector of size 373
@@ -137,7 +137,7 @@ NULL
 #' @format a data frame with 15132 rows and two variables
 #' @name abisko
 #' @source Abisko Scientific Research Station
-#' @references A. Kiriliouk, H. Rootzén, J. Segers and J.L. Wadsworth (2019), \emph{Peaks over thresholds modeling With multivariate generalized Pareto distributions},  Technometrics, \bold{61}(1), 123--135, \code{DOI:10.1080/00401706.2018.1462738}
+#' @references A. Kiriliouk, H. Rootzen, J. Segers and J.L. Wadsworth (2019), \emph{Peaks over thresholds modeling with multivariate generalized Pareto distributions},  Technometrics, \bold{61}(1), 123--135, <doi:10.1080/00401706.2018.1462738>
 NULL
 
 #' Nutrient data

R/tailindex.R

@@ -8,7 +8,7 @@
 #' The calculations are based on the recursions provided in Lemma 4.3 of Oorschot et al.
 #' @param xdat vector of observations of length \eqn{n}
 #' @param m number of largest order statistics \eqn{3 \leq m \leq n}. Choosing \eqn{m = n} amounts to using only the three largest observations in the sample.
-#' @references Oorschot, J, J. Segers and C. Zhou (2023+), Tail inference using extreme U-statistics
+#' @references Oorschot, J, J. Segers and C. Zhou (2023), Tail inference using extreme U-statistics,  Electron. J. Statist. 17(1): 1113-1159. \doi{10.1214/23-EJS2129}
 #' @export
 #' @examples
 #' samp <- rgp(n = 1000, shape = 0.2)