Updated vignettes

andrewzm · Mar 29, 2019 · 4d379dd · 4d379dd
1 parent bc6df7d
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Showing 7 changed files with 306 additions and 266 deletions.
diff --git a/R/EFDR_functions.R b/R/EFDR_functions.R
@@ -34,7 +34,7 @@
 #'
 #' @examples
 #' ## See vignettes by typing vignette("EFDR_vignettes")
-test.efdr <- function(Z,wf = "la8",J=3, alpha=0.05,n.hyp=100,b=11,iteration = 200, parallel = 1L)
+test.efdr <- function(Z,wf = "la8",J=2, alpha=0.05,n.hyp=100,b=11,iteration = 200, parallel = 1L)
 {
 
   .check_args(Z = Z,wf = wf,J = J,alpha = alpha,n.hyp = n.hyp,b = b,iteration = iteration,parallel = parallel)
@@ -52,7 +52,7 @@ test.efdr <- function(Z,wf = "la8",J=3, alpha=0.05,n.hyp=100,b=11,iteration = 20
   test.efdr.base(Z, wf=wf,J=J, alpha = alpha, n.hyp = nhat, b=b, nei=nei)
 }
 
-test.efdr.base <- function(Z,wf = "la8",J=3, alpha=0.05,n.hyp=100,b=11,nei = NULL, parallel = 1L)
+test.efdr.base <- function(Z,wf = "la8",J=2, alpha=0.05,n.hyp=100,b=11,nei = NULL, parallel = 1L)
 {
   .check_args(Z = Z,wf = wf,J = J,alpha = alpha,n.hyp = n.hyp,b = b,nei = nei, parallel = parallel)
 
@@ -98,7 +98,7 @@ test.efdr.base <- function(Z,wf = "la8",J=3, alpha=0.05,n.hyp=100,b=11,nei = NUL
 
 #' @rdname wavelet-test
 #' @export
-test.fdr <- function(Z,wf = "la8",J=3,alpha=0.05)
+test.fdr <- function(Z,wf = "la8",J=2,alpha=0.05)
 {
 
   .check_args(Z = Z,wf = wf,J = J,alpha = alpha)
@@ -138,7 +138,7 @@ test.fdr <- function(Z,wf = "la8",J=3,alpha=0.05)
 
 #' @rdname wavelet-test
 #' @export
-test.bonferroni <- function(Z,wf="la8",J=3,alpha=0.05)
+test.bonferroni <- function(Z,wf="la8",J=2,alpha=0.05)
 {
 
   .check_args(Z = Z,wf = wf,J = J,alpha = alpha)
@@ -172,7 +172,7 @@ test.bonferroni <- function(Z,wf="la8",J=3,alpha=0.05)
 
 #' @rdname wavelet-test
 #' @export
-test.los <- function(Z,wf="la8",J=3,alpha=0.05)
+test.los <- function(Z,wf="la8",J=2,alpha=0.05)
 {
   .check_args(Z = Z,wf = wf,J = J,alpha = alpha)
 
@@ -260,7 +260,7 @@ test_image <- function(h=1,r=10,n1 = 64, n2=64)   {
 #' @examples
 #' Z <- test_image(h = 0.5, r = 14, n1 = 64)$z
 #' print(wav_th(Z,wf="la8",J=3,th=0.5))
-wav_th <- function(Z, wf = "la8", J = 3, th = 1) {
+wav_th <- function(Z, wf = "la8", J = 2, th = 1) {
   stopifnot(is.numeric(th))
   .check_args(Z = Z,wf = wf,J = J)
 
@@ -527,7 +527,7 @@ diagnostic.table <- function(reject.true,reject, n) {
 #' @examples
 #' image <- matrix(rnorm(64),8,8)
 #  nei <- nei.efdr(image,b=11)
-nei.efdr <- function(Z,wf="la8",J=3,b=11,parallel=1L) {
+nei.efdr <- function(Z,wf="la8",J=2,b=11,parallel=1L) {
 
   .check_args(Z=Z,wf=wf,J=J,b=b,parallel=parallel)
 
@@ -573,7 +573,7 @@ nei.efdr <- function(Z,wf="la8",J=3,b=11,parallel=1L) {
 }
 
 ### check input arguments
-.check_args <- function(Z,wf="la8",J=3,alpha = 0.05,n.hyp = 1L,b = 11L,nei = NULL,iteration = 1L,parallel=1L) {
+.check_args <- function(Z,wf="la8",J=2,alpha = 0.05,n.hyp = 1L,b = 11L,nei = NULL,iteration = 1L,parallel=1L) {
   if(!is.matrix(Z)) stop("Z needs to be a matrix")
   #if(!(ncol(Z) == nrow(Z))) stop("Z needs to be square")
   if(!(.IsPowerOfTwo(ncol(Z))) |  !(.IsPowerOfTwo(nrow(Z)))) stop("Z needs to have rows and columns a power of two")
@@ -598,7 +598,7 @@ nei.efdr <- function(Z,wf="la8",J=3,b=11,parallel=1L) {
 }
 
 ### function to find the L*
-.gdf <- function(Z, wf = "la8", J = 3, alpha = 0.05, n.hyp=c(100,150,200),iteration=200,b=11,nei=NULL,parallel=1L)
+.gdf <- function(Z, wf = "la8", J = 2, alpha = 0.05, n.hyp=c(100,150,200),iteration=200,b=11,nei=NULL,parallel=1L)
 {
 
   stopifnot(is.numeric(iteration))

diff --git a/inst/doc/EFDR.Rmd b/inst/doc/EFDR.Rmd
@@ -50,7 +50,7 @@ fields::image.plot(Z_noisy,zlim=c(-0.5,1.5),asp=1)
 Next, the user needs to provide some essential parameters. These are
 - `alpha`:    significance level
 - `wf`:       wavelet name (typically "la8")
-- `J`:        number of multi-level resolutions (for a 64 x 64, 3 is sufficient)
+- `J`:        number of multi-level resolutions (for a 64 x 64, 3 is usually sufficient)
 - `b`:        number of neighbours to consider with EFDR
 - `n.hyp`:    numeric vector of test counts, from which the optimal number of tests, $L^*$, will be found. Setting this to a scalar fixes the number of tests a priori
 - `iteration`:  number of iterations in the Monte Carlo integration described earlier
@@ -177,7 +177,7 @@ First, load the dataset using RCurl:
 ```{r,message=FALSE,cache=FALSE}
 library(RCurl)
 airs.raw <- read.table(textConnection(getURL(
-                "http://hpc.niasra.uow.edu.au/ckan/dataset/6ddf61bb-2f9a-424a-8775-e23ebaa55afb/resource/e1206e1c-9dca-42b6-8455-3cdd98c6a943/download/airs2003may116.csv"
+                "https://hpc.niasra.uow.edu.au/ckan/dataset/6ddf61bb-2f9a-424a-8775-e23ebaa55afb/resource/e1206e1c-9dca-42b6-8455-3cdd98c6a943/download/airs2003may116.csv"
                 )),header=T,sep=",")
 ```