R version 4.4.0 RC (2024-04-16 r86441 ucrt) -- "Puppy Cup"
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Platform: x86_64-w64-mingw32/x64

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> require(lokern)
Loading required package: lokern
> data(xSim)
> (n <- length(xSim))
[1] 75
> summary(xSim)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
-3.1323 -1.6148  0.7583  0.3969  1.7713  4.4505 
> tt <- ((1:n) - 1/2)/n # equidistant x
> 
> lk  <- lokerns(tt, xSim, trace=1)
lokerns (n=75,m=300; nue=0, isrand=1, inputp=0) -> kord=2
 phase  2
 phase  3
 phase  4
 40: itt=0, (il=1, iu=75) -  (tl=1, tu=0)
 phase  5
 phase  6
 phase  7
 phase  8
 phase  9
 phase 10
  100: (il=6, iu=70) -> vi=0.115996
 phase 11
 kernel(n= 75, m= 76, ny=0 => global bandw.; b=0.01000531) -> (chg.pt,cut_b)=( 7.0, 0.09) => 'classic'
 phase 12
 phase 18
 phase 19
 phase 20
 kernel(n= 75, m=300, ny=1 => local bandw.; b=0.04845241) -> (chg.pt,cut_b)=( 7.0, 0.09) => 'classic'
 phase 21
 kernel(n= 75, m=399, ny=0 => global bandw.; b= 0.0611626) -> (chg.pt,cut_b)=( 9.0, 0.12) => 'classic'
 kernp(n=399, m=300, ny=1 => local bandw.; b=  0.086814) -> (chg.pt,cut_b)=( 8.1, 0.02) => 'fast O(n)'
  kernfp(n=399, b=  0.086814, nue=0, kord=2, ny=1, m=300):
 phase 22
 phase 23
 kernel(n= 75, m=300, ny=1 => local bandw.; b=0.04845241) -> (chg.pt,cut_b)=( 7.0, 0.09) => 'classic'
> head(x. <- seq(-3.5, 4.5, length=1001))
[1] -3.500 -3.492 -3.484 -3.476 -3.468 -3.460
> lk.  <- lokerns(tt, xSim, x.out= x., trace=1)
lokerns (n=75,m=1001; nue=0, isrand=1, inputp=0) -> kord=2
 phase  2
 phase  3
 phase  4
 40: itt=0, (il=1, iu=75) -  (tl=1, tu=0)
 phase  5
 phase  6
 phase  7
 phase  8
 phase  9
 phase 10
  100: (il=6, iu=70) -> vi=0.115996
 phase 11
 kernel(n= 75, m= 76, ny=0 => global bandw.; b=0.01000531) -> (chg.pt,cut_b)=( 7.0, 0.09) => 'classic'
 phase 12
 phase 18
 phase 19
 phase 20
 kernel(n= 75, m=1001, ny=1 => local bandw.; b=0.04845241) -> (chg.pt,cut_b)=( 7.0, 0.09) => 'classic'
 phase 21
 kernel(n= 75, m=399, ny=0 => global bandw.; b= 0.0611626) -> (chg.pt,cut_b)=( 9.0, 0.12) => 'classic'
 kernp(n=399, m=1001, ny=1 => local bandw.; b=  0.086814) -> (chg.pt,cut_b)=( 7.0, 0.14) => 'classic'
 phase 22
 phase 23
 kernel(n= 75, m=1001, ny=1 => local bandw.; b=0.04845241) -> (chg.pt,cut_b)=( 7.0, 0.09) => 'classic'
> lkw <- tryCatch(lokerns(tt, xSim, x.out= x., x.inOut="aim"),
+                 warning = function(.) .)
> stopifnot(inherits(lkw, "simpleWarning"),
+ 	  grepl("x.inOut", lkw[["message"]]))
> 
> lkn. <- lokerns(tt, xSim, n.out= 1000, x.inOut=FALSE)
> lknT <- lokerns(tt, xSim, n.out= 1000, x.inOut=TRUE)
> lkn1 <- lokerns(tt, xSim, n.out= 1000, x.inOut="aim")
> lkn2 <- lokerns(tt, xSim, n.out= 1000, x.inOut="simple")
> lkn3 <- lokerns(tt, xSim, n.out= 1000, x.inOut="interpolate")
> 
> iO <- which("call" != names(lkn.))
> stopifnot(all.equal(lknT[iO],
+ 		    lkn1[iO], tol=1e-12),
+           inherits(try(residuals(lkn.), silent=TRUE), "try-error"),
+           length(residuals(lkn1)) == length(tt),
+           length(fitted   (lkn2)) == length(tt),
+           TRUE)
> pdf("lok-xout-ex.pdf")
> 
> plot(tt, xSim, main = "data + 4 different lokerns(.., x.inOut = *)")
> lines(est~x.out, data=lk. [c("x.out", "est")])
> lines(est~x.out, data=lkn1[c("x.out", "est")], col=2)
> lines(est~x.out, data=lkn2[c("x.out", "est")], col=3)
> lines(est~x.out, data=lkn3[c("x.out", "est")], col=4)
> mtext("(you should not see different curves -- rather perfectly overlap")
> 
> gkn. <- glkerns(tt, xSim, n.out= 1000, x.inOut=FALSE)
> gknT <- glkerns(tt, xSim, n.out= 1000, x.inOut=TRUE)
> gkn1 <- glkerns(tt, xSim, n.out= 1000, x.inOut="aim")
> gkn2 <- glkerns(tt, xSim, n.out= 1000, x.inOut="simple")
> gkn3 <- glkerns(tt, xSim, n.out= 1000, x.inOut="interpolate")
> 
> plot(tt, xSim, main = "data + 4 different glkerns(.., x.inOut = *)")
> lines(est~x.out, data=gkn.[c("x.out", "est")])
> lines(est~x.out, data=gkn1[c("x.out", "est")], col=2)
> lines(est~x.out, data=gkn2[c("x.out", "est")], col=3)
> lines(est~x.out, data=gkn3[c("x.out", "est")], col=4)
> mtext("(you should not see different curves -- rather perfectly overlap")
> 
> stopifnot(all(sapply(ls(patt="kn"), function(.)get(.)$sig) -
+ 	      0.145106481 < 5e-10))
> 
> cat('Time elapsed: ', proc.time(),'\n') # "stats"
Time elapsed:  0.23 0.07 0.29 NA NA 
> 
> proc.time()
   user  system elapsed 
   0.23    0.07    0.29