Updated.

git-svn-id: https://svn.r-project.org/R/trunk@88742 00db46b3-68df-0310-9c12-caf00c1e9a41

Author: hornik

src/library/stats/tests/ks-test.R

@@ -72,10 +72,11 @@ sapply(pv$s0, unlist)
 sapply(pv$s., unlist) # not really close, but ..
 
 pv$s0$two.sided[1] <-  1 ## artificially
-stopifnot(all.equal(pv$s0, pv$s., tol = 0.5 + 1e-6), # seen 0.5
+stopifnot(all.equal(pv$s0, pv$s., tolerance = 0.5 + 1e-6), # seen 0.5
 	  ## "less" are close:
 	  all.equal(unlist(pv[[c("s0","less")]]),
-		    unlist(pv[[c("s.","less")]]), tol = 0.03),
+		    unlist(pv[[c("s.","less")]]),
+                    tolerance = 0.03),
 	  0 <= unlist(pv), unlist(pv) <= 1) # <- no further NA ..
 ## b)
 sapply(stR[["statistic"]], unlist)

src/library/stats/tests/ks-test.Rout.save

@@ -1,7 +1,7 @@
 
-R Under development (unstable) (2023-04-19 r84284) -- "Unsuffered Consequences"
-Copyright (C) 2023 The R Foundation for Statistical Computing
-Platform: aarch64-apple-darwin22.4.0 (64-bit)
+R Under development (unstable) (2025-08-29 r88740) -- "Unsuffered Consequences"
+Copyright (C) 2025 The R Foundation for Statistical Computing
+Platform: x86_64-pc-linux-gnu
 
 R is free software and comes with ABSOLUTELY NO WARRANTY.
 You are welcome to redistribute it under certain conditions.
@@ -170,17 +170,19 @@ $s.[[5]]
 +                               wilcox.test(x, exact=TRUE, conf.int=TRUE, alternative = alt)
 +                               ## )
 +                               )))
-There were 52 warnings (use warnings() to see them)
+There were 55 warnings (use warnings() to see them)
 > length(ww <- warnings()) # 52 (or 43 for x0 <- 0:3)
-[1] 52
+[1] 55
 > unique(ww) # 4 different ones
 Warning messages:
-1: In wilcox.test.default(x, exact = TRUE, conf.int = TRUE,  ... :
-  cannot compute exact p-value with zeroes
+1: cannot compute confidence interval when all observations are zero or tied
 2: In wilcox.test.default(x, exact = TRUE, conf.int = TRUE,  ... :
+  cannot compute exact p-value with zeroes
+3: In wilcox.test.default(x, exact = TRUE, conf.int = TRUE,  ... :
   cannot compute exact confidence interval with zeroes
-3: cannot compute confidence interval when all observations are zero or tied
-4: In wilcox.test.default(x, exact = TRUE, conf.int = TRUE,  ... :
+4: In .wilcox_test_one_cint_asymp(x, n, alternative, conf.level,  ... :
+  requested conf.level not achievable
+5: In .wilcox_test_one_cint_exact(x, n, alternative, conf.level) :
   requested conf.level not achievable
 > 
 > cc <- lapply(RR, function(A) lapply(A, function(bb) lapply(bb, class)))
@@ -225,10 +227,11 @@ character(0)
 [5,]    0.0625    1 0.03125
 > 
 > pv$s0$two.sided[1] <-  1 ## artificially
-> stopifnot(all.equal(pv$s0, pv$s., tol = 0.5 + 1e-6), # seen 0.5
+> stopifnot(all.equal(pv$s0, pv$s., tolerance = 0.5 + 1e-6), # seen 0.5
 + 	  ## "less" are close:
 + 	  all.equal(unlist(pv[[c("s0","less")]]),
-+ 		    unlist(pv[[c("s.","less")]]), tol = 0.03),
++ 		    unlist(pv[[c("s.","less")]]),
++                     tolerance = 0.03),
 + 	  0 <= unlist(pv), unlist(pv) <= 1) # <- no further NA ..
 > ## b)
 > sapply(stR[["statistic"]], unlist)
@@ -252,21 +255,21 @@ greater.V   10 15
 > ## c)
 > sapply(stR[["estimate" ]], unlist)
                           s0      s.
-two.sided1               NaN 1.0e-09
-two.sided.midrange       1.0 5.0e-01
-two.sided.(pseudo)median 1.5 1.0e+00
-two.sided.(pseudo)median 2.0 1.5e+00
-two.sided.(pseudo)median 2.5 2.0e+00
-less1                    NaN 1.0e-09
-less.midrange            1.0 5.0e-01
-less.(pseudo)median      1.5 1.0e+00
-less.(pseudo)median      2.0 1.5e+00
-less.(pseudo)median      2.5 2.0e+00
-greater1                 NaN 1.0e-09
-greater.midrange         1.0 5.0e-01
-greater.(pseudo)median   1.5 1.0e+00
-greater.(pseudo)median   2.0 1.5e+00
-greater.(pseudo)median   2.5 2.0e+00
+two.sided.midrange       0.0 1.0e-09
+two.sided.(pseudo)median 0.5 5.0e-01
+two.sided.(pseudo)median 1.0 1.0e+00
+two.sided.(pseudo)median 1.5 1.5e+00
+two.sided.(pseudo)median 2.0 2.0e+00
+less.midrange            0.0 1.0e-09
+less.(pseudo)median      0.5 5.0e-01
+less.(pseudo)median      1.0 1.0e+00
+less.(pseudo)median      1.5 1.5e+00
+less.(pseudo)median      2.0 2.0e+00
+greater.midrange         0.0 1.0e-09
+greater.(pseudo)median   0.5 5.0e-01
+greater.(pseudo)median   1.0 1.0e+00
+greater.(pseudo)median   1.5 1.5e+00
+greater.(pseudo)median   2.0 2.0e+00
 > ## d) confidence interval
 > formatCI <- function(ci)
 +     sprintf("[%g, %g] (%g%%)", ci[[1]], ci[[2]],
@@ -277,12 +280,18 @@ greater.(pseudo)median   2.5 2.0e+00
 +     matrix("", nx, length(alts))))
 , , s0
 
-     two.sided                less                  greater             
-[1,] [NaN, NaN] (0%)          [-Inf, NaN] (0%)      [NaN, Inf] (0%)     
-[2,] [NaN, NaN] (0%)          [-Inf, NaN] (0%)      [NaN, Inf] (0%)     
-[3,] [1.5, 1.5] (0%)          [-Inf, 1.5] (0%)      [1.50001, Inf] (20%)
-[4,] [1.00007, 2.99993] (60%) [-Inf, 2.00002] (60%) [1.00009, Inf] (80%)
-[5,] [1.00006, 3.99994] (80%) [-Inf, 3.00002] (80%) [1.00009, Inf] (90%)
+     two.sided                    less                 
+[1,] [NaN, NaN] (0%)              [-Inf, NaN] (0%)     
+[2,] [0.5, 0.5] (0%)              [-Inf, 0.5] (0%)     
+[3,] [6.57258e-05, 1.99993] (60%) [-Inf, 1.00002] (60%)
+[4,] [5.6384e-05, 2.99994] (80%)  [-Inf, 2.00002] (80%)
+[5,] [0.999997, 3] (80%)          [-Inf, 2.99998] (80%)
+     greater                 
+[1,] [NaN, Inf] (0%)         
+[2,] [0.500007, Inf] (20%)   
+[3,] [8.76344e-05, Inf] (80%)
+[4,] [9.39734e-05, Inf] (90%)
+[5,] [0.999983, Inf] (90%)   
 
 , , s.
 
@@ -307,7 +316,7 @@ There were 27 warnings (use warnings() to see them)
 [1] 27
 > unique(w2) # 3 different ones
 Warning messages:
-1: In wilcox.test.default(x = x.set$s0[[k]], y = x.set$s.[[k]],  ... :
+1: In .wilcox_test_two_cint_exact(x, y, n.x, n.y, alternative,  ... :
   Requested conf.level not achievable
 2: In wilcox.test.default(x = x.set$s0[[k]], y = x.set$s.[[k]],  ... :
   cannot compute exact p-value with ties
@@ -362,4 +371,4 @@ difference in location  3.741417e-05  3.741417e-05  3.741417e-05
 > 
 > proc.time()
    user  system elapsed 
-  0.130   0.017   0.145 
+  0.246   0.024   0.250