update v1.2.3

zejiang-unsw · Nov 27, 2021 · 2914059 · 2914059
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commit 2914059
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diff --git a/.DS_Store b/.DS_Store
diff --git a/R/data_gen_AR.R b/R/data_gen_AR.R
@@ -11,6 +11,9 @@
 #' # AR1 model from paper with 9 dummy variables
 #' data.ar1<-data.gen.ar1(500)
 #' plot.ts(cbind(data.ar1$x,data.ar1$dp))
+#'
+#' # Predictor Identifier
+#' NPRED::stepwise.PIC(data.ar1$x, data.ar1$dp)
 
 data.gen.ar1 <- function(nobs, ndim = 9) {
     nwarm <- 500
@@ -42,6 +45,11 @@ data.gen.ar1 <- function(nobs, ndim = 9) {
 #' # AR4 model from paper with total 9 dimensions
 #' data.ar4<-data.gen.ar4(500)
 #' plot.ts(cbind(data.ar4$x,data.ar4$dp))
+#'
+#'\donttest{
+#' # Predictor Identifier
+#' NPRED::stepwise.PIC(data.ar4$x, data.ar4$dp)
+#' }
 
 data.gen.ar4 <- function(nobs, ndim = 9) {
     nwarm <- 500
@@ -73,6 +81,11 @@ data.gen.ar4 <- function(nobs, ndim = 9) {
 #' # AR9 model from paper with total 9 dimensions
 #' data.ar9<-data.gen.ar9(500)
 #' plot.ts(cbind(data.ar9$x,data.ar9$dp))
+#'
+#'\donttest{
+#' # Predictor Identifier
+#' NPRED::stepwise.PIC(data.ar9$x, data.ar9$dp)
+#' }
 
 data.gen.ar9 <- function(nobs, ndim = 9) {
     nwarm <- 500

diff --git a/R/data_gen_Chaotic.R b/R/data_gen_Chaotic.R
@@ -53,6 +53,27 @@
 #' plot(ts.r$x,ts.r$y, xlab='x',ylab = 'y', type = 'l')
 #' plot(ts.r$x,ts.r$z, xlab='x',ylab = 'z', type = 'l')
 #' par(oldpar)
+#'
+#' \donttest{
+#' # Application to testing variance transformation method in:
+#' # Jiang, Z., Sharma, A., & Johnson, F. (2020) <doi:10.1029/2019WR026962>
+#' data <- list(x = ts.r$z, dp = cbind(ts.r$x, ts.r$y))
+#' dwt <- WASP::dwt.vt(data, wf="d4", J=7, method="dwt", pad="zero", boundary="periodic")
+#'
+#' par(mfrow = c(ncol(dwt$dp), 1), mar = c(0, 2.5, 2, 1),
+#'     oma = c(2, 1, 0, 0), # move plot to the right and up
+#'     mgp = c(1.5, 0.5, 0), # move axis labels closer to axis
+#'     pty = "m", bg = "transparent",
+#'     ps = 12)
+#'
+#' # plot(dwt$x, type="l", xlab=NA, ylab="SPI12", col="red")
+#' # plot(dwt$x, type="l", xlab=NA, ylab="Rain", col="red")
+#' for (i in 1:ncol(dwt$dp)) {
+#'   ts.plot(cbind(dwt$dp[, i], dwt$dp.n[, i]),
+#'           xlab = NA, ylab = NA,
+#'           col = c("black", "blue"), lwd = c(1, 2))
+#' }
+#' }
 
 data.gen.Rossler <- function(a = 0.2, b = 0.2, w = 5.7, start = c(-2, -10, 0.2),
     time = seq(0, by = 0.05, length.out = 1000), s) {

diff --git a/cran-comments.md b/cran-comments.md
@@ -1,6 +1,6 @@
 ## Test environments
-* local R installation, R 4.0.5
-* ubuntu 16.04 (on travis-ci), R 4.0.5
+* local R installation, R 4.1.0
+* ubuntu 16.04 (on travis-ci), R 4.1.0
 * win-builder (devel)
 
 ## R CMD check results

diff --git a/inst/.DS_Store b/inst/.DS_Store
diff --git a/inst/apa-six-edition.csl b/inst/apa-six-edition.csl
diff --git a/man/data.gen.Rossler.Rd b/man/data.gen.Rossler.Rd
diff --git a/man/data.gen.ar1.Rd b/man/data.gen.ar1.Rd
diff --git a/man/data.gen.ar4.Rd b/man/data.gen.ar4.Rd
diff --git a/man/data.gen.ar9.Rd b/man/data.gen.ar9.Rd
diff --git a/vignettes/synthesis.Rmd b/vignettes/synthesis.Rmd
@@ -10,6 +10,7 @@ vignette: >
   %\VignetteEncoding{UTF-8}
   
 bibliography: ../inst/synthesis.bib
+
 ---
 
 ```{r, include = FALSE}
@@ -364,3 +365,4 @@ plot.zoo(cbind(p, data.tss$x, data.tss$y), xlab=NA,
          ylab=c("Q","Bulid-up","Wash-off"), main="TSS")
 
 ```
+