update reference outputs with r88215

git-svn-id: https://svn.r-project.org/R/trunk@88216 00db46b3-68df-0310-9c12-caf00c1e9a41

Author: smeyer

tests/Examples/datasets-Ex.Rout.save

@@ -1,5 +1,5 @@
 
-R Under development (unstable) (2025-05-15 r88204) -- "Unsuffered Consequences"
+R Under development (unstable) (2025-05-18 r88215) -- "Unsuffered Consequences"
 Copyright (C) 2025 The R Foundation for Statistical Computing
 Platform: x86_64-pc-linux-gnu
 
@@ -895,6 +895,11 @@ Residual standard error: 3.803 on 45 degrees of freedom
 Multiple R-squared:  0.3385,	Adjusted R-squared:  0.2797 
 F-statistic: 5.756 on 4 and 45 DF,  p-value: 0.0007904
 
+> 
+> ## recreate pre-4.6 dataset with a misspelled row name
+> idx <- which(row.names(LifeCycleSavings) == "Guatemala")
+> stopifnot(length(idx) == 1)
+> LCS <- LifeCycleSavings; row.names(LCS)[idx] <- "Guatamala" # sic!
 > 
 > 
 > 
@@ -3994,7 +3999,7 @@ c0   -5.14
 > cleanEx()
 > options(digits = 7L)
 > base::cat("Time elapsed: ", proc.time() - base::get("ptime", pos = 'CheckExEnv'),"\n")
-Time elapsed:  2.05 0.135 2.209 0 0 
+Time elapsed:  2.798 0.094 2.893 0 0 
 > grDevices::dev.off()
 null device 
           1 

tests/Examples/stats-Ex.Rout.save

@@ -1,7 +1,7 @@
 
-R Under development (unstable) (2025-04-22 r88173) -- "Unsuffered Consequences"
+R Under development (unstable) (2025-05-18 r88215) -- "Unsuffered Consequences"
 Copyright (C) 2025 The R Foundation for Statistical Computing
-Platform: aarch64-apple-darwin24.2.0
+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.
@@ -1266,16 +1266,16 @@ Residual standard error: 0.04103 on 7 degrees of freedom
 +         nls(conc ~ SSbiexp(time, A1, lrc1, A2, lrc2), data = datN,
 +             trace=TRUE, control = list(maxiter = 10)) )
 0.01722077  (5.34e+02): par = (0.6168807 -1.783839 2.050204 0.2004597)
-3.308944e-06 (1.13e+04): par = (0.5798674 -1.784335 2.028943 0.1920502)
-2.571079e-11 (7.68e+06): par = (0.5793882 -1.78778 2.029276 0.1915479)
-1.650535e-23 (2.91e+03): par = (0.5793887 -1.787785 2.029277 0.1915475)
-3.486470e-28 (9.76e-01): par = (0.5793887 -1.787785 2.029277 0.1915475)
-3.475413e-28 (1.03e+00): par = (0.5793887 -1.787785 2.029277 0.1915475)
-3.425893e-28 (5.48e-01): par = (0.5793887 -1.787785 2.029277 0.1915475)
-3.425893e-28 (5.48e-01): par = (0.5793887 -1.787785 2.029277 0.1915475)
-3.425893e-28 (5.48e-01): par = (0.5793887 -1.787785 2.029277 0.1915475)
-3.425893e-28 (5.48e-01): par = (0.5793887 -1.787785 2.029277 0.1915475)
-3.425893e-28 (5.48e-01): par = (0.5793887 -1.787785 2.029277 0.1915475)
+3.308943e-06 (1.13e+04): par = (0.5798674 -1.784335 2.028943 0.1920502)
+2.571069e-11 (7.68e+06): par = (0.5793882 -1.78778 2.029276 0.1915479)
+1.669346e-23 (5.53e+03): par = (0.5793887 -1.787785 2.029277 0.1915475)
+2.285755e-29 (1.59e+01): par = (0.5793887 -1.787785 2.029277 0.1915475)
+1.345909e-29 (1.20e+01): par = (0.5793887 -1.787785 2.029277 0.1915475)
+1.224242e-29 (9.63e+00): par = (0.5793887 -1.787785 2.029277 0.1915475)
+1.224242e-29 (9.63e+00): par = (0.5793887 -1.787785 2.029277 0.1915475)
+1.224242e-29 (9.63e+00): par = (0.5793887 -1.787785 2.029277 0.1915475)
+1.224242e-29 (9.63e+00): par = (0.5793887 -1.787785 2.029277 0.1915475)
+1.224242e-29 (9.63e+00): par = (0.5793887 -1.787785 2.029277 0.1915475)
 Error in nls(y ~ cbind(exp(-exp(lrc1) * x), exp(-exp(lrc2) * x)), data = xy,  : 
   number of iterations exceeded maximum of 10
 > ## End(Don't show)
@@ -1288,13 +1288,13 @@ Error in nls(y ~ cbind(exp(-exp(lrc1) * x), exp(-exp(lrc2) * x)), data = xy,  :
 3.308942e-06  (9.08e-04): par = (0.5798674 -1.784335 2.028943 0.1920502)
   It.   2, fac=           1, eval (no.,total): ( 1,  2): new dev = 2.57108e-11
 2.571081e-11  (2.53e-06): par = (0.5793882 -1.78778 2.029276 0.1915479)
-  It.   3, fac=           1, eval (no.,total): ( 1,  3): new dev = 1.66968e-23
-1.669677e-23  (2.04e-12): par = (0.5793887 -1.787785 2.029277 0.1915475)
-1.667503e-23  (1.67e-13): par = (2.029277 0.5793887 0.1915475 -1.787785)
+  It.   3, fac=           1, eval (no.,total): ( 1,  3): new dev = 1.66926e-23
+1.669257e-23  (2.04e-12): par = (0.5793887 -1.787785 2.029277 0.1915475)
+1.670550e-23  (1.67e-13): par = (2.029277 0.5793887 0.1915475 -1.787785)
 > all.equal(coef(fm1), coef(fmX1), tolerance=0) # ... rel.diff.: 1.57e-6
-[1] "Mean relative difference: 1.574121e-06"
+[1] "Mean relative difference: 1.574118e-06"
 > all.equal(coef(fm1), coef(fmX),  tolerance=0) # ... rel.diff.: 1.03e-12
-[1] "Mean relative difference: 1.031016e-12"
+[1] "Mean relative difference: 1.032123e-12"
 > ## IGNORE_RDIFF_END
 > stopifnot(all.equal(coef(fm1), coef(fmX1), tolerance = 6e-6),
 +           all.equal(coef(fm1), coef(fmX ), tolerance = 1e-11))
@@ -5124,7 +5124,7 @@ function (V)
         r[seq.int(from = 1L, by = p + 1L, length.out = p)] <- 1
     r
 }
-<bytecode: 0x12090f330>
+<bytecode: 0x6192cd5d48d0>
 <environment: namespace:stats>
 > stopifnot(all.equal(Cl, cov2cor(cov(longley))),
 +           all.equal(cor(longley, method = "kendall"),
@@ -7772,7 +7772,7 @@ attr(,".Environment")
 > environment(as.formula("y ~ x"))
 <environment: R_GlobalEnv>
 > environment(as.formula("y ~ x", env = new.env()))
-<environment: 0x10699fb68>
+<environment: 0x6192cccb1d48>
 > 
 > 
 > ## Create a formula for a model with a large number of variables:
@@ -8598,7 +8598,7 @@ Finland               -113   111   117  -44   -17
 France                -166   147   219  -29    24
 Germany                 -8     8     8   -7     0
 Greece                -148   164    29  157   -60
-Guatamala               16   -55     6    6    97
+Guatemala               16   -55     6    6    97
 Honduras                -2    10   -10    8    -2
 Iceland                248  -274  -233 -126   185
 India                   21   -16   -14  -14   -19
@@ -9020,23 +9020,23 @@ totss        60.99123 60.99123
 > ## The ordering of the clusters may be platform-dependent.
 > ## IGNORE_RDIFF_BEGIN
 > (cl <- kmeans(x, 5, nstart = 25))
-K-means clustering with 5 clusters of sizes 12, 15, 25, 24, 24
+K-means clustering with 5 clusters of sizes 12, 24, 24, 15, 25
 
 Cluster means:
            x          y
 1  1.3290081  1.1185534
-2  0.8609139  1.3145869
-3 -0.1096832  0.2106891
-4  0.1581362 -0.1761590
-5  0.8043520  0.7805033
+2  0.1581362 -0.1761590
+3  0.8043520  0.7805033
+4  0.8609139  1.3145869
+5 -0.1096832  0.2106891
 
 Clustering vector:
-  [1] 3 4 3 4 3 3 4 4 3 3 5 4 3 3 4 3 4 3 4 3 4 4 3 3 4 3 4 3 3 4 4 4 3 4 3 3 3
- [38] 4 4 4 4 3 3 3 3 3 4 4 4 4 2 5 5 5 5 1 1 1 5 1 2 5 1 2 5 2 5 5 1 2 2 1 2 5
- [75] 5 1 2 2 2 2 5 2 1 5 1 5 2 5 5 5 5 1 5 2 5 5 1 5 2 5
+  [1] 5 2 5 2 5 5 2 2 5 5 3 2 5 5 2 5 2 5 2 5 2 2 5 5 2 5 2 5 5 2 2 2 5 2 5 5 5
+ [38] 2 2 2 2 5 5 5 5 5 2 2 2 2 4 3 3 3 3 1 1 1 3 1 4 3 1 4 3 4 3 3 1 4 4 1 4 3
+ [75] 3 1 4 4 4 4 3 4 1 3 1 3 4 3 3 3 3 1 3 4 3 3 1 3 4 3
 
 Within cluster sum of squares by cluster:
-[1] 1.0314888 0.7104553 2.5330710 1.2816507 1.5056575
+[1] 1.0314888 1.2816507 1.5056575 0.7104553 2.5330710
  (between_SS / total_SS =  88.4 %)
 
 Available components:
@@ -11350,16 +11350,16 @@ Initializing ‘Const’, ‘A’, ‘B’ to '1.'.
 Consider specifying 'start' or using a selfStart model
 1017460.306    (4.15e+02): par = (1 1 1)
 758164.7503    (2.34e+02): par = (13.42031396 1.961485 0.05947543745)
-269506.3538    (3.23e+02): par = (51.75719816 -13.09155956 0.8428607705)
-68969.21895    (1.03e+02): par = (76.0006985 -1.935226741 1.019085799)
-633.3672233    (1.29e+00): par = (100.3761515 8.624648407 5.104490263)
-151.4400223    (9.39e+00): par = (100.6344391 4.913490982 0.2849209561)
-53.08739887    (7.24e+00): par = (100.6830407 6.899303309 0.4637755073)
-1.344478645    (5.97e-01): par = (100.0368306 9.897714142 0.516929494)
+269506.3539    (3.23e+02): par = (51.75719815 -13.09155956 0.8428607704)
+68969.21896    (1.03e+02): par = (76.0006985 -1.93522674 1.019085799)
+633.3672231    (1.29e+00): par = (100.3761515 8.624648403 5.104490265)
+151.4400225    (9.39e+00): par = (100.6344391 4.913490981 0.2849209558)
+53.08739902    (7.24e+00): par = (100.6830407 6.899303306 0.4637755073)
+1.344478646    (5.97e-01): par = (100.0368306 9.897714142 0.516929494)
 0.9908415909   (1.55e-02): par = (100.0300625 9.9144191 0.5023516843)
 0.9906046057   (1.84e-05): par = (100.0288724 9.916224018 0.5025207337)
-0.9906046054   (9.93e-08): par = (100.028875 9.916228366 0.50252165)
-0.9906046054   (6.56e-10): par = (100.028875 9.916228388 0.5025216549)
+0.9906046054   (9.94e-08): par = (100.028875 9.916228366 0.50252165)
+0.9906046054   (5.87e-10): par = (100.028875 9.916228388 0.5025216549)
 Nonlinear regression model
   model: y ~ Const + A * exp(B * x)
    data: parent.frame()
@@ -12714,14 +12714,14 @@ attr(,"class")
 $linkfun
 function (mu) 
 mu^lambda
-<bytecode: 0x12056a680>
-<environment: 0x120575bb0>
+<bytecode: 0x6192ce2df040>
+<environment: 0x6192cfc8fda8>
 
 $linkinv
 function (eta) 
 pmax(eta^(1/lambda), .Machine$double.eps)
-<bytecode: 0x12056a530>
-<environment: 0x120575bb0>
+<bytecode: 0x6192ce2deda0>
+<environment: 0x6192cfc8fda8>
 
 > 
 > 
@@ -16177,7 +16177,7 @@ Contrast 1 Contrast 2 Contrast 3
 > getInitial(weight ~ mySSlogis(Time, Asym, xmid, scal),
 +            data = subset(ChickWeight, Chick == 1))
      Asym      xmid      scal 
-937.03000  35.22296  11.40521 
+937.03011  35.22296  11.40521 
 > ## IGNORE_RDIFF_END
 > 
 > # 'first.order.log.model' is a function object defining a first order
@@ -17080,8 +17080,8 @@ Step function with continuity 'f'= 0.2 ,  3 knots at
 > unclass(sfun0)
 function (v) 
 .approxfun(x, y, v, method, yleft, yright, f, na.rm)
-<bytecode: 0x115d97208>
-<environment: 0x106858c98>
+<bytecode: 0x6192cdaa8ef0>
+<environment: 0x6192ce371420>
 attr(,"call")
 stepfun(1:3, y0, f = 0)
 > ls(envir = environment(sfun0))
@@ -19676,7 +19676,7 @@ Number of Fisher Scoring iterations: 6
 > cleanEx()
 > options(digits = 7L)
 > base::cat("Time elapsed: ", proc.time() - base::get("ptime", pos = 'CheckExEnv'),"\n")
-Time elapsed:  2.846 0.215 3.067 0 0 
+Time elapsed:  5.444 0.237 5.681 0 0 
 > grDevices::dev.off()
 null device 
           1 

tests/lm-tests.Rout.save

@@ -1,7 +1,7 @@
 
-R Under development (unstable) (2022-12-20 r83481) -- "Unsuffered Consequences"
-Copyright (C) 2022 The R Foundation for Statistical Computing
-Platform: x86_64-pc-linux-gnu (64-bit)
+R Under development (unstable) (2025-05-18 r88215) -- "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.
@@ -131,7 +131,7 @@ Finland        -0.11350  0.11133  0.11695 -0.04364 -0.017132 -0.1464 1.203
 France         -0.16600  0.14705  0.21900 -0.02942  0.023952  0.2765 1.226
 Germany        -0.00802  0.00822  0.00835 -0.00697 -0.000293 -0.0152 1.226
 Greece         -0.14820  0.16394  0.02861  0.15713 -0.059599 -0.2811 1.140
-Guatamala       0.01552 -0.05485  0.00614  0.00585  0.097217 -0.2305 1.085
+Guatemala       0.01552 -0.05485  0.00614  0.00585  0.097217 -0.2305 1.085
 Honduras       -0.00226  0.00984 -0.01020  0.00812 -0.001887  0.0482 1.186
 Iceland         0.24789 -0.27355 -0.23265 -0.12555  0.184698 -0.4768 0.866
 India           0.02105 -0.01577 -0.01439 -0.01374 -0.018958  0.0381 1.202
@@ -182,7 +182,7 @@ Finland        4.36e-03 0.0920
 France         1.55e-02 0.1362    
 Germany        4.74e-05 0.0874    
 Greece         1.59e-02 0.0966    
-Guatamala      1.07e-02 0.0605    
+Guatemala      1.07e-02 0.0605    
 Honduras       4.74e-04 0.0601    
 Iceland        4.35e-02 0.0705    
 India          2.97e-04 0.0715    
@@ -253,7 +253,7 @@ Finland            -0.8420  1.62e-02  0.12800 -4.10e-05 -3.39e-03
 France             -1.2300  2.14e-02  0.23900 -2.76e-05  4.73e-03
 Germany            -0.0597  1.20e-03  0.00915 -6.56e-06 -5.82e-05
 Greece             -1.0900  2.38e-02  0.03110  1.47e-04 -1.17e-02
-Guatamala           0.1140 -7.95e-03  0.00667  5.46e-06  1.91e-02
+Guatemala           0.1140 -7.95e-03  0.00667  5.46e-06  1.91e-02
 Honduras           -0.0168  1.44e-03 -0.01120  7.64e-06 -3.74e-04
 Iceland             1.7800 -3.87e-02 -0.24700 -1.14e-04  3.55e-02
 India               0.1560 -2.31e-03 -0.01580 -1.29e-05 -3.76e-03
@@ -294,7 +294,7 @@ Malaysia            0.2720 -8.88e-03  0.03520 -4.63e-05 -1.42e-02
      1.3283009      0.6547098      1.1498637      1.1666845      0.9681384 
        Denmark        Ecuador        Finland         France        Germany 
      0.9344047      1.1393880      1.2031561      1.2262654      1.2256855 
-        Greece      Guatamala       Honduras        Iceland          India 
+        Greece      Guatemala       Honduras        Iceland          India 
      1.1396174      1.0852720      1.1855450      0.8658808      1.2024438 
        Ireland          Italy          Japan          Korea     Luxembourg 
      1.2680432      1.1624611      1.0845999      0.8695843      1.1961844