[Distr-commits] r1398 - in branches/distr-2.9/pkg/distr: . man tests/Examples
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Mon Nov 14 20:47:34 CET 2022
Author: ruckdeschel
Date: 2022-11-14 20:47:34 +0100 (Mon, 14 Nov 2022)
New Revision: 1398
Added:
branches/distr-2.9/pkg/distr/tests/Examples/distr-Ex.Rout.save
Removed:
branches/distr-2.9/pkg/distr/tests/Examples/distr-Ex_i386.Rout.save
branches/distr-2.9/pkg/distr/tests/Examples/distr-Ex_x64.Rout.save
Modified:
branches/distr-2.9/pkg/distr/DESCRIPTION
branches/distr-2.9/pkg/distr/man/0distr-package.Rd
branches/distr-2.9/pkg/distr/man/MinMaximum-methods.Rd
branches/distr-2.9/pkg/distr/man/RtoDPQ.Rd
branches/distr-2.9/pkg/distr/man/RtoDPQ.d.Rd
branches/distr-2.9/pkg/distr/man/qqplot.Rd
branches/distr-2.9/pkg/distr/man/simplifyr-methods.Rd
Log:
[distr] Version 2.9.1 (new fuzz acc. to BDR)
Modified: branches/distr-2.9/pkg/distr/DESCRIPTION
===================================================================
--- branches/distr-2.9/pkg/distr/DESCRIPTION 2022-11-14 19:46:00 UTC (rev 1397)
+++ branches/distr-2.9/pkg/distr/DESCRIPTION 2022-11-14 19:47:34 UTC (rev 1398)
@@ -1,6 +1,6 @@
Package: distr
-Version: 2.9.1
-Date: 2022-11-12
+Version: 2.9.2
+Date: 2022-11-14
Title: Object Oriented Implementation of Distributions
Description: S4-classes and methods for distributions.
Authors at R: c(person("Florian", "Camphausen", role="ctb", comment="contributed as student in
Modified: branches/distr-2.9/pkg/distr/man/0distr-package.Rd
===================================================================
--- branches/distr-2.9/pkg/distr/man/0distr-package.Rd 2022-11-14 19:46:00 UTC (rev 1397)
+++ branches/distr-2.9/pkg/distr/man/0distr-package.Rd 2022-11-14 19:47:34 UTC (rev 1398)
@@ -44,8 +44,8 @@
\details{
\tabular{ll}{
Package: \tab distr \cr
-Version: \tab 2.8.1 \cr
-Date: \tab 2022-11-12 \cr
+Version: \tab 2.9.1 \cr
+Date: \tab 2022-11-14 \cr
Depends: \tab R(>= 3.4), methods, graphics, startupmsg, sfsmisc \cr
Suggests: \tab distrEx, svUnit (>= 0.7-11), knitr, distrMod, ROptEst \cr
Imports: \tab stats, grDevices, utils, MASS \cr
@@ -52,7 +52,7 @@
LazyLoad: \tab yes \cr
License: \tab LGPL-3 \cr
URL: \tab https://distr.r-forge.r-project.org/\cr
-VCS/SVNRevision: \tab 1369 \cr
+VCS/SVNRevision: \tab 1395 \cr
}}
\section{Classes}{
Distribution classes have a slot \code{param} the class of which
Modified: branches/distr-2.9/pkg/distr/man/MinMaximum-methods.Rd
===================================================================
--- branches/distr-2.9/pkg/distr/man/MinMaximum-methods.Rd 2022-11-14 19:46:00 UTC (rev 1397)
+++ branches/distr-2.9/pkg/distr/man/MinMaximum-methods.Rd 2022-11-14 19:47:34 UTC (rev 1398)
@@ -76,8 +76,10 @@
}}
\seealso{\code{\link{Huberize}}, \code{\link{Truncate}}}
\examples{
+## IGNORE_RDIFF_BEGIN
plot(Maximum(Unif(0,1), Minimum(Unif(0,1), Unif(0,1))))
plot(Minimum(Exp(4),4))
+## IGNORE_RDIFF_END
## a sometimes lengthy example...
\donttest{plot(Minimum(Norm(),Pois()))}
}
Modified: branches/distr-2.9/pkg/distr/man/RtoDPQ.Rd
===================================================================
--- branches/distr-2.9/pkg/distr/man/RtoDPQ.Rd 2022-11-14 19:46:00 UTC (rev 1397)
+++ branches/distr-2.9/pkg/distr/man/RtoDPQ.Rd 2022-11-14 19:47:34 UTC (rev 1398)
@@ -49,7 +49,9 @@
# returns density, cumulative distribution and quantile function of
# squared standard normal distribution
x$dfun(4)
+## IGNORE_RDIFF_BEGIN
RtoDPQ(r = rn2, e = 5, n = 1024) # for a better result
+## IGNORE_RDIFF_END
rp2 <- function(n){rpois(n, lambda = 1)^2}
x <- RtoDPQ.d(r = rp2, e = 5)
Modified: branches/distr-2.9/pkg/distr/man/RtoDPQ.d.Rd
===================================================================
--- branches/distr-2.9/pkg/distr/man/RtoDPQ.d.Rd 2022-11-14 19:46:00 UTC (rev 1397)
+++ branches/distr-2.9/pkg/distr/man/RtoDPQ.d.Rd 2022-11-14 19:47:34 UTC (rev 1398)
@@ -43,7 +43,9 @@
# squared standard normal distribution
x$dfun(4)
+## IGNORE_RDIFF_BEGIN
RtoDPQ(r = rn2, e = 5, n = 1024) # for a better result
+## IGNORE_RDIFF_END
rp2 <- function(n){rpois(n, lambda = 1)^2}
x <- RtoDPQ.d(r = rp2, e = 5)
Modified: branches/distr-2.9/pkg/distr/man/qqplot.Rd
===================================================================
--- branches/distr-2.9/pkg/distr/man/qqplot.Rd 2022-11-14 19:46:00 UTC (rev 1397)
+++ branches/distr-2.9/pkg/distr/man/qqplot.Rd 2022-11-14 19:47:34 UTC (rev 1398)
@@ -142,6 +142,7 @@
Peter Ruckdeschel \email{peter.ruckdeschel at uni-oldenburg.de}
}
\examples{
+## IGNORE_RDIFF_BEGIN
qqplot(Norm(15,sqrt(30)), Chisq(df=15))
## some discrete Distributions:
P <- Pois(5)
@@ -166,6 +167,7 @@
mylist4 <- UnivarMixingDistribution(Unif(0,0.3),Unif(0.6,1),mixCoeff=c(0.6,0.4))
qqplot(mylist3,mylist4)
qqplot(mylist3,mylist4,nosym.pCI=TRUE)
+## IGNORE_RDIFF_END
}
}
\keyword{hplot}
Modified: branches/distr-2.9/pkg/distr/man/simplifyr-methods.Rd
===================================================================
--- branches/distr-2.9/pkg/distr/man/simplifyr-methods.Rd 2022-11-14 19:46:00 UTC (rev 1397)
+++ branches/distr-2.9/pkg/distr/man/simplifyr-methods.Rd 2022-11-14 19:47:34 UTC (rev 1398)
@@ -22,10 +22,14 @@
\examples{
F <- ( Norm() + Binom() + Pois() + Exp() ) * 2 - 10
+## IGNORE_RDIFF_BEGIN
system.time(r(F)(10^6))
+## IGNORE_RDIFF_END
simplifyr(F, size = 10^6)
-system.time(r(F)(10^6))}
-
+## IGNORE_RDIFF_BEGIN
+system.time(r(F)(10^6))
+## IGNORE_RDIFF_END
+}
\keyword{math}
\keyword{distribution}
\keyword{arith}
Added: branches/distr-2.9/pkg/distr/tests/Examples/distr-Ex.Rout.save
===================================================================
--- branches/distr-2.9/pkg/distr/tests/Examples/distr-Ex.Rout.save (rev 0)
+++ branches/distr-2.9/pkg/distr/tests/Examples/distr-Ex.Rout.save 2022-11-14 19:47:34 UTC (rev 1398)
@@ -0,0 +1,3891 @@
+
+R Under development (unstable) (2022-09-25 r82916 ucrt) -- "Unsuffered Consequences"
+Copyright (C) 2022 The R Foundation for Statistical Computing
+Platform: x86_64-w64-mingw32/x64 (64-bit)
+
+R is free software and comes with ABSOLUTELY NO WARRANTY.
+You are welcome to redistribute it under certain conditions.
+Type 'license()' or 'licence()' for distribution details.
+
+ Natural language support but running in an English locale
+
+R is a collaborative project with many contributors.
+Type 'contributors()' for more information and
+'citation()' on how to cite R or R packages in publications.
+
+Type 'demo()' for some demos, 'help()' for on-line help, or
+'help.start()' for an HTML browser interface to help.
+Type 'q()' to quit R.
+
+> pkgname <- "distr"
+> source(file.path(R.home("share"), "R", "examples-header.R"))
+> options(warn = 1)
+> options(pager = "console")
+> library('distr')
+Loading required package: startupmsg
+:startupmsg> Utilities for Start-Up Messages (version 0.9.6)
+:startupmsg>
+:startupmsg> For more information see ?"startupmsg",
+:startupmsg> NEWS("startupmsg")
+
+Loading required package: sfsmisc
+:distr> Object Oriented Implementation of Distributions (version
+:distr> 2.9.1)
+:distr>
+:distr> Attention: Arithmetics on distribution objects are
+:distr> understood as operations on corresponding random variables
+:distr> (r.v.s); see distrARITH().
+:distr>
+:distr> Some functions from package 'stats' are intentionally masked
+:distr> ---see distrMASK().
+:distr>
+:distr> Note that global options are controlled by distroptions()
+:distr> ---c.f. ?"distroptions".
+:distr>
+:distr> For more information see ?"distr", NEWS("distr"), as well as
+:distr> http://distr.r-forge.r-project.org/
+:distr> Package "distrDoc" provides a vignette to this package as
+:distr> well as to several extension packages; try
+:distr> vignette("distr").
+
+
+Attaching package: 'distr'
+
+The following objects are masked from 'package:stats':
+
+ df, qqplot, sd
+
+>
+> base::assign(".oldSearch", base::search(), pos = 'CheckExEnv')
+> base::assign(".old_wd", base::getwd(), pos = 'CheckExEnv')
+> cleanEx()
+> nameEx("0distr-package")
+> ### * 0distr-package
+>
+> flush(stderr()); flush(stdout())
+>
+> ### Name: distr-package
+> ### Title: distr - Object Oriented Implementation of Distributions
+> ### Aliases: distr-package distr
+> ### Keywords: package distribution
+>
+> ### ** Examples
+>
+> X <- Unif(2,3)
+> Y <- Pois(lambda = 3)
+> Z <- X+Y # generates Law of corresponding independent variables
+> p(Z)(0.2)
+[1] 0
+> r(Z)(1000)
+ [1] 6.579102 4.779275 3.372658 4.632594 3.217653 2.833188 5.836883
+ [8] 4.328749 6.265813 2.547148 6.076999 8.133506 3.549124 7.967771
+ [15] 4.282188 5.334846 5.539449 5.441803 3.869821 6.553436 6.532861
+ [22] 8.883538 5.557134 7.066122 5.258768 2.550905 6.796403 3.145013
+ [29] 3.486209 5.707381 6.944007 3.826960 6.383630 8.323171 8.907333
+ [36] 7.056447 2.114501 4.904405 6.198231 5.835608 2.628063 6.578858
+ [43] 3.072209 7.283379 4.889372 5.162274 4.432173 5.755494 4.371829
+ [50] 4.179435 3.676957 3.343576 3.335259 5.945975 5.712469 4.512781
+ [57] 3.670003 6.359885 6.723871 5.154257 4.752679 3.084680 6.164728
+ [64] 5.980637 5.935260 5.065854 2.531672 4.055380 4.378224 5.166891
+ [71] 6.558560 6.743660 6.059266 7.432974 7.402949 4.851098 6.300433
+ [78] 8.925874 3.993535 4.602505 4.957766 2.634655 7.653118 3.972603
+ [85] 5.345732 3.754893 5.776172 8.286398 8.446992 7.560786 6.635046
+ [92] 8.711620 4.107038 4.367655 8.993393 4.432253 10.929256 4.073590
+ [99] 5.577728 7.706458 7.484063 6.119480 3.191338 3.039565 3.491861
+ [106] 5.339283 4.443054 3.735495 3.518061 6.380735 9.683830 4.579353
+ [113] 6.700189 6.147659 3.976503 5.340870 9.642431 4.107585 4.609351
+ [120] 4.178274 5.338655 5.502983 5.574192 3.938589 5.164298 9.568823
+ [127] 6.277261 7.587950 3.822969 3.486584 5.308142 6.057207 3.523045
+ [134] 5.481863 4.357590 3.278691 5.547702 4.912094 2.255964 4.017637
+ [141] 5.827255 6.049479 7.595250 3.981267 6.569439 6.727461 4.151836
+ [148] 5.318238 6.699690 4.854844 4.378279 5.275432 8.988444 2.134025
+ [155] 5.977953 2.642202 5.600517 4.162107 7.143829 3.762430 5.781959
+ [162] 4.217105 4.714697 4.293084 7.271073 5.903164 3.934551 6.452999
+ [169] 3.329169 5.398796 4.169447 6.209014 5.827562 6.347140 5.599187
+ [176] 6.452403 5.093153 7.896114 6.262903 2.711165 4.249534 5.896619
+ [183] 9.174417 5.468117 2.795493 2.341466 3.478540 3.260784 6.985835
+ [190] 4.438382 5.730667 5.680872 5.907649 4.760867 6.853652 8.254687
+ [197] 4.453843 4.784929 4.591713 2.988044 5.927597 5.885563 4.569294
+ [204] 6.919895 6.290173 4.256231 3.720954 7.162789 3.482136 4.980341
+ [211] 7.714786 7.603208 2.756598 7.042582 3.892577 7.766692 5.472288
+ [218] 5.897596 5.407148 2.767171 5.941631 8.765190 6.650673 3.923338
+ [225] 4.270002 5.960052 6.441325 4.262422 3.362592 8.902643 9.294795
+ [232] 3.214329 7.052151 7.936144 7.840518 6.612929 6.048513 4.269719
+ [239] 7.760647 7.917457 6.042595 4.623126 6.025792 7.996861 2.177719
+ [246] 6.654859 4.661239 3.820550 7.876687 6.082439 5.830691 4.417018
+ [253] 5.066648 3.104336 6.731124 4.594065 5.534583 6.048505 4.615337
+ [260] 9.738851 3.117800 10.366602 2.135035 5.297118 5.908073 2.112919
+ [267] 6.564549 6.008583 4.787502 11.807161 6.509220 8.478424 6.403077
+ [274] 5.543653 6.007867 5.173895 2.896862 5.519487 4.973214 5.805484
+ [281] 5.949032 6.285357 5.619059 5.795161 6.935567 4.526653 5.831893
+ [288] 4.800116 6.658077 4.995597 4.845622 4.879891 6.482920 4.094898
+ [295] 5.028267 6.009440 4.823092 7.043040 10.823171 4.091859 4.864138
+ [302] 4.022668 10.050640 2.949141 6.228148 4.626769 5.439620 4.599773
+ [309] 6.968634 4.994205 3.273534 4.287168 9.199977 10.196245 9.991003
+ [316] 6.955347 5.506245 4.236431 3.517317 5.577783 3.218334 7.222556
+ [323] 4.825124 4.363241 4.924039 3.320962 5.120049 5.210499 4.559181
+ [330] 3.403327 2.789545 6.471046 3.873281 7.176098 4.305160 5.395722
+ [337] 7.004994 4.898506 4.424281 4.020754 3.632583 4.253636 7.789985
+ [344] 5.114602 7.069107 4.200499 3.293541 9.391404 5.353941 4.003051
+ [351] 2.304293 3.531214 6.863910 8.259209 2.093975 4.083890 4.257744
+ [358] 2.086540 6.117788 3.186305 3.069495 5.338623 6.860354 7.781543
+ [365] 6.277202 4.723161 4.633321 6.156335 5.152739 4.158852 6.895088
+ [372] 8.289939 4.018619 2.049620 5.593186 3.241354 3.304142 4.794494
+ [379] 5.750661 6.589345 3.136211 4.627482 5.864843 2.597692 4.197970
+ [386] 4.982050 3.131675 8.181336 8.788943 5.236139 5.860343 6.419425
+ [393] 8.651857 3.579700 5.323007 6.431335 3.417773 4.522973 4.432197
+ [400] 8.182775 5.070290 5.964844 9.542852 4.748663 4.554676 9.680594
+ [407] 7.250223 10.284465 4.126663 5.693831 7.880095 7.968802 3.317698
+ [414] 4.045398 6.949944 5.400209 5.371284 3.324154 3.560770 6.091314
+ [421] 7.774884 5.413062 4.823627 4.365933 3.883124 3.245356 3.594525
+ [428] 4.365887 9.745536 6.011345 8.925059 4.869513 5.638617 8.295089
+ [435] 8.935575 3.663063 5.618220 8.561209 3.176157 5.520921 6.711753
+ [442] 7.925893 4.067052 7.236690 7.695405 4.332264 4.113306 4.939782
+ [449] 7.372087 5.706058 7.751002 6.403756 4.227362 4.273287 6.072921
+ [456] 4.910409 2.459842 7.600472 4.275654 6.973216 6.873162 9.751179
+ [463] 4.136125 6.655204 2.080379 6.265311 4.223805 3.498867 4.924211
+ [470] 5.800581 4.806109 6.664286 2.229823 3.286322 6.061472 3.949581
+ [477] 7.649938 5.617929 6.072907 7.494375 6.440831 8.013917 7.248682
+ [484] 7.171046 5.345439 7.456406 6.654902 6.953591 5.726936 5.247356
+ [491] 3.613288 5.128787 5.052366 4.567321 5.740011 5.750754 9.352847
+ [498] 7.125697 4.866561 4.069580 6.650475 4.244731 4.329885 3.274329
+ [505] 4.979835 7.913374 4.674176 6.326536 7.148619 6.579086 5.477506
+ [512] 7.960702 3.157628 4.002058 6.086027 5.238919 5.590526 4.435348
+ [519] 5.597217 8.762081 5.789205 9.470844 5.934225 8.645870 4.665628
+ [526] 6.270418 6.502792 8.638165 3.534610 7.806940 7.806592 4.497164
+ [533] 4.166165 8.547377 5.185010 5.847412 7.154381 5.697753 3.821394
+ [540] 8.387257 5.753594 7.799001 6.051941 4.888510 6.764761 7.341601
+ [547] 4.123064 4.173528 3.565936 4.346350 6.853956 4.203341 3.216346
+ [554] 5.590785 5.713518 4.339589 5.375326 9.243176 5.887737 2.112778
+ [561] 5.742362 4.044285 5.720649 3.863230 5.039876 5.721132 6.326835
+ [568] 3.726445 3.032174 4.372235 6.415886 4.121232 7.407248 4.424386
+ [575] 4.357479 6.830058 5.365814 6.293699 2.374506 3.719549 2.100653
+ [582] 6.691715 8.235638 4.779743 6.282059 3.706763 6.619718 6.544563
+ [589] 7.924641 3.531242 4.271171 3.905814 8.020223 6.779150 7.364992
+ [596] 5.307303 4.160868 3.176943 5.693852 2.621652 6.468918 5.869892
+ [603] 3.693521 4.506954 5.913281 4.812330 6.404537 6.794142 4.017008
+ [610] 5.548779 6.254126 6.253319 4.624762 4.090745 6.460816 2.913422
+ [617] 4.485198 3.388693 4.171777 3.677474 3.292837 6.075759 5.719630
+ [624] 7.132900 2.991177 8.098001 5.837644 4.548980 4.983142 5.703874
+ [631] 4.281914 6.253390 3.177424 6.002899 5.454130 6.992385 7.816874
+ [638] 8.066406 4.898936 4.829592 3.024088 3.472519 7.272335 7.336495
+ [645] 3.057295 5.205245 5.869878 5.940514 4.960493 4.123543 6.881292
+ [652] 5.565367 5.532138 4.599130 7.057423 3.152381 7.322148 5.617132
+ [659] 6.080236 4.957499 4.928580 5.950919 7.106630 4.557867 5.742990
+ [666] 4.342305 5.370324 5.661521 5.077816 4.189266 7.408123 4.212645
+ [673] 9.980272 5.455587 6.955461 5.027057 4.040872 6.516094 5.102335
+ [680] 4.762621 5.161881 5.168592 7.857960 4.060331 4.329365 5.821864
+ [687] 5.446692 4.958970 4.770069 6.251505 5.219794 4.975353 6.647226
+ [694] 8.646266 2.638373 4.096875 7.459760 5.963888 4.921418 3.200894
+ [701] 4.305496 6.087948 3.489525 6.390110 5.178165 8.226200 7.341701
+ [708] 3.126380 7.065164 4.277436 2.600411 6.273144 4.941489 4.799276
+ [715] 4.089915 4.392771 6.174850 3.456753 7.481765 5.142862 4.034420
+ [722] 4.202052 6.264259 4.744758 3.353447 5.877194 4.135481 5.570409
+ [729] 8.412244 4.225636 4.797575 6.398676 2.591563 6.906964 5.384810
+ [736] 6.371892 5.374292 6.182153 3.041935 6.261203 10.304963 2.178528
+ [743] 5.558146 7.371060 4.642810 5.924116 3.259350 6.239350 3.848965
+ [750] 4.699012 6.884430 7.209243 4.528550 5.228070 8.102115 4.102062
+ [757] 3.150018 2.116710 5.626661 5.515649 2.670773 6.861331 4.636687
+ [764] 9.570007 7.894844 8.275016 4.490435 7.946827 6.142462 5.174121
+ [771] 7.886910 3.507694 6.190410 5.562037 4.547680 3.893744 6.704781
+ [778] 5.561152 7.447658 6.105691 4.658082 7.168129 5.486573 5.167835
+ [785] 3.129796 6.416057 5.255846 4.693766 5.249084 5.958214 8.764405
+ [792] 3.841370 5.875610 2.009616 7.036117 3.285925 6.080532 4.968795
+ [799] 8.564562 6.984705 5.836639 6.880194 3.244425 7.732067 4.498606
+ [806] 6.503376 4.568116 4.652677 8.064712 11.676612 4.735372 3.111300
+ [813] 3.046655 6.130910 4.880956 6.839725 2.868143 3.033383 6.107907
+ [820] 6.549297 8.109318 6.722591 7.725010 4.789522 9.617478 3.503007
+ [827] 4.456149 3.034666 6.209639 5.342787 3.545595 7.769484 4.428765
+ [834] 3.686462 5.521869 5.796536 3.903052 6.432457 6.331940 6.917115
+ [841] 5.209280 5.812735 4.300713 7.572182 5.386782 8.279482 5.260043
+ [848] 5.959384 5.634133 8.081877 3.926206 5.890943 5.912085 5.718499
+ [855] 3.682528 5.555186 6.401709 5.863838 2.074414 5.283284 11.162637
+ [862] 2.763897 5.116376 3.167472 3.475884 4.005788 5.974413 2.114148
+ [869] 2.080774 5.322919 5.118785 9.985772 2.404148 6.241782 4.354879
+ [876] 4.153240 5.287548 6.256672 4.157690 7.029772 4.811628 6.579173
+ [883] 6.576732 2.701487 6.063766 3.502483 3.383950 5.426416 5.544390
+ [890] 6.643638 3.791192 3.846853 4.072626 7.860111 6.956165 5.926419
+ [897] 3.053964 5.246409 6.487370 6.100063 4.195159 6.213572 5.207682
+ [904] 6.028771 8.234566 3.107185 5.277316 2.696022 4.266257 4.660477
+ [911] 7.212417 5.005266 4.102903 6.287400 8.444156 6.692993 7.020884
+ [918] 6.955752 6.804111 5.911740 5.309467 7.323928 4.138360 6.957561
+ [925] 2.232669 5.023715 7.052112 4.932720 5.038752 6.807114 4.696882
+ [932] 4.388051 4.390583 5.982333 3.216765 8.566960 5.980336 6.574558
+ [939] 4.632867 7.782993 2.856876 5.041593 5.895225 4.188517 2.387342
+ [946] 7.494502 4.370316 6.693625 3.733155 4.308550 6.972442 5.243334
+ [953] 5.835028 7.390576 8.908864 6.607566 5.607495 6.894327 2.975288
+ [960] 7.676351 5.091139 3.777949 7.517544 6.652370 5.339298 5.292120
+ [967] 6.783712 2.319966 5.489278 5.134142 5.653294 4.783924 6.921809
+ [974] 8.258464 4.513233 5.858583 3.151414 5.641468 3.825477 7.972295
+ [981] 4.173126 4.710022 6.110715 7.416779 9.284621 4.341155 5.168895
+ [988] 3.547097 3.797206 6.858631 6.332270 3.515725 3.371685 4.436701
+ [995] 5.742429 10.011101 6.046900 4.371818 6.658157 7.529650
+> plot(Z+sin(Norm()))
+>
+>
+> cleanEx()
+> nameEx("AbscontDistribution-class")
+> ### * AbscontDistribution-class
+>
+> flush(stderr()); flush(stdout())
+>
+> ### Name: AbscontDistribution-class
+> ### Title: Class "AbscontDistribution"
+> ### Aliases: AbscontDistribution-class AffLinDistribution-class
+> ### AffLinAbscontDistribution-class sqrt,AbscontDistribution-method
+> ### initialize,AbscontDistribution-method
+> ### initialize,AffLinAbscontDistribution-method
+> ### sqrt,AbscontDistribution-method
+> ### Keywords: distribution
+>
+> ### ** Examples
+>
+> N <- Norm() # N is a normal distribution with mean=0 and sd=1.
+> E <- Exp() # E is an exponential distribution with rate=1.
+> A1 <- E+1 # a new absolutely continuous distributions with exact slots d, p, q
+> A2 <- A1*3 # a new absolutely continuous distributions with exact slots d, p, q
+> A3 <- N*0.9 + E*0.1 # a new absolutely continuous distribution with approximated slots d, p, q
+> r(A3)(1) # one random number generated from this distribution, e.g. -0.7150937
+[1] -0.5492378
+> d(A3)(0) # The (approximated) density for x=0 is 0.43799.
+[1] 0.4379965
+> p(A3)(0) # The (approximated) probability that x <= 0 is 0.45620.
+[1] 0.4561991
+> q(A3)(.1) # The (approximated) 10 percent quantile is -1.06015.
+[1] -1.060145
+> ## in RStudio or Jupytier IRKernel, use q.l(.)(.) instead of q(.)(.)
+>
+>
+>
+> cleanEx()
+> nameEx("AbscontDistribution")
+> ### * AbscontDistribution
+>
+> flush(stderr()); flush(stdout())
+>
+> ### Name: AbscontDistribution
+> ### Title: Generating function "AbscontDistribution"
+> ### Aliases: AbscontDistribution
+> ### Keywords: distribution
+>
+> ### ** Examples
+>
+> plot(Norm())
+> plot(AbscontDistribution(r = rnorm))
+> plot(AbscontDistribution(d = dnorm))
+> plot(AbscontDistribution(p = pnorm))
+> plot(AbscontDistribution(q = qnorm))
+> plot(Ac <- AbscontDistribution(d = function(x, log = FALSE){
++ d <- exp(-abs(x^3))
++ ## unstandardized!!
++ if(log) d <- log(d)
++ return(d)},
++ withStand = TRUE))
+>
+>
+>
+> cleanEx()
+> nameEx("Arcsine-class")
+> ### * Arcsine-class
+>
+> flush(stderr()); flush(stdout())
+>
+> ### Name: Arcsine-class
+> ### Title: Class "Arcsine"
+> ### Aliases: Arcsine-class Arcsine initialize,Arcsine-method
+> ### Keywords: distribution
+>
+> ### ** Examples
+>
+> A <- Arcsine()
+> # A is a Arcsine distribution with shape1 = 1 and shape2 = 1.
+> r(A)(3) # three random number generated from this distribution, e.g. 0.6979795
+[1] -0.6718297 -0.3910154 0.2268826
+> d(A)(c(-2,-1,-0.2,0,0.2,1,2)) # Density at x=c(-1,-0.2,0,0.2,1).
+[1] 0.0000000 Inf 0.3248737 0.3183099 0.3248737 Inf 0.0000000
+> p(A)(c(-2,-1,-0.2,0,0.2,1,2)) # cdf at q=c(-1,-0.2,0,0.2,1).
+[1] 0.0000000 0.0000000 0.4359058 0.5000000 0.5640942 1.0000000 1.0000000
+> q(A)(c(0,0.2,1,2)) # quantile function at at x=c(0,0.2,1).
+[1] -1.000000 -0.809017 1.000000 NA
+> ## in RStudio or Jupyter IRKernel, use q.l(A)(c(0,0.2,1,2)) instead
+>
+>
+>
+> cleanEx()
+> nameEx("Beta-class")
+> ### * Beta-class
+>
+> flush(stderr()); flush(stdout())
+>
+> ### Name: Beta-class
+> ### Title: Class "Beta"
+> ### Aliases: Beta-class Beta initialize,Beta-method
+> ### Keywords: distribution
+>
+> ### ** Examples
+>
+> B <- Beta(shape1 = 1, shape2 = 1)
+> # B is a beta distribution with shape1 = 1 and shape2 = 1.
+> r(B)(1) # one random number generated from this distribution, e.g. 0.6979795
+[1] 0.07614139
+> d(B)(1) # Density of this distribution is 1 for x=1.
+[1] 1
+> p(B)(1) # Probability that x < 1 is 1.
+[1] 1
+> q(B)(.1) # Probability that x < 0.1 is 0.1.
+[1] 0.1
+> shape1(B) # shape1 of this distribution is 1.
+[1] 1
+> shape1(B) <- 2 # shape1 of this distribution is now 2.
+> Bn <- Beta(shape1 = 1, shape2 = 3, ncp = 5)
+> # Bn is a beta distribution with shape1 = 1 and shape2 = 3 and ncp = 5.
+> B0 <- Bn; ncp(B0) <- 0;
+> # B0 is just the same beta distribution as Bn but with ncp = 0
+> q(B0)(0.1) ##
+[1] 0.03451062
+> q(Bn)(0.1) ## => from R 2.3.0 on ncp no longer ignored...
+[1] 0.2047932
+> ## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
+>
+>
+>
+> cleanEx()
+> nameEx("BetaParameter-class")
+> ### * BetaParameter-class
+>
+> flush(stderr()); flush(stdout())
+>
+> ### Name: BetaParameter-class
+> ### Title: Class "BetaParameter"
+> ### Aliases: BetaParameter-class initialize,BetaParameter-method
+> ### Keywords: distribution
+>
+> ### ** Examples
+>
+> W <- new("BetaParameter", shape1 = 1, shape2 = 1, ncp = 0)
+> shape2(W) # shape2 of this distribution is 1.
+[1] 1
+> shape2(W) <- 2 # shape2 of this distribution is now 2.
+>
+>
+>
+> cleanEx()
+> nameEx("Binom-class")
+> ### * Binom-class
+>
+> flush(stderr()); flush(stdout())
+>
+> ### Name: Binom-class
+> ### Title: Class "Binom"
+> ### Aliases: Binom-class Binom initialize,Binom-method
+> ### Keywords: distribution
+>
+> ### ** Examples
+>
+> B <- Binom(prob=0.5,size=1) # B is a binomial distribution with prob=0.5 and size=1.
+> r(B)(1) # # one random number generated from this distribution, e.g. 1
+[1] 0
+> d(B)(1) # Density of this distribution is 0.5 for x=1.
+[1] 0.5
+> p(B)(0.4) # Probability that x<0.4 is 0.5.
+[1] 0.5
+> q(B)(.1) # x=0 is the smallest value x such that p(B)(x)>=0.1.
+[1] 0
+> ## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
+> size(B) # size of this distribution is 1.
+[1] 1
+> size(B) <- 2 # size of this distribution is now 2.
+> C <- Binom(prob = 0.5, size = 1) # C is a binomial distribution with prob=0.5 and size=1.
+> D <- Binom(prob = 0.6, size = 1) # D is a binomial distribution with prob=0.6 and size=1.
+> E <- B + C # E is a binomial distribution with prob=0.5 and size=3.
+> F <- B + D # F is an object of class LatticeDistribution.
+> G <- B + as(D,"DiscreteDistribution") ## DiscreteDistribution
+>
+>
+>
+> cleanEx()
+> nameEx("BinomParameter-class")
+> ### * BinomParameter-class
+>
+> flush(stderr()); flush(stdout())
+>
+> ### Name: BinomParameter-class
+> ### Title: Class "BinomParameter"
+> ### Aliases: BinomParameter-class initialize,BinomParameter-method
+> ### Keywords: distribution
+>
+> ### ** Examples
+>
+> W <- new("BinomParameter",prob=0.5,size=1)
+> size(W) # size of this distribution is 1.
+[1] 1
+> size(W) <- 2 # size of this distribution is now 2.
+>
+>
+>
+> cleanEx()
+> nameEx("Cauchy-class")
+> ### * Cauchy-class
+>
+> flush(stderr()); flush(stdout())
+>
+> ### Name: Cauchy-class
+> ### Title: Class "Cauchy"
+> ### Aliases: Cauchy-class Cauchy initialize,Cauchy-method
+> ### Keywords: distribution
+>
+> ### ** Examples
+>
+> C <- Cauchy(location = 1, scale = 1) # C is a Cauchy distribution with location=1 and scale=1.
+> r(C)(1) # one random number generated from this distribution, e.g. 4.104603
+[1] 2.10252
+> d(C)(1) # Density of this distribution is 0.3183099 for x=1.
+[1] 0.3183099
+> p(C)(1) # Probability that x<1 is 0.5.
+[1] 0.5
+> q(C)(.1) # Probability that x<-2.077684 is 0.1.
+[1] -2.077684
+> ## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
+> location(C) # location of this distribution is 1.
+[1] 1
+> location(C) <- 2 # location of this distribution is now 2.
+> is(C,"Td") # no
+[1] FALSE
+> C0 <- Cauchy() # standard, i.e. location = 0, scale = 1
+> is(C0,"Td") # yes
+[1] TRUE
+> as(C0,"Td")
+Distribution Object of Class: Td
+ df: 1
+ ncp: 0
+>
+>
+>
+> cleanEx()
+> nameEx("CauchyParameter-class")
+> ### * CauchyParameter-class
+>
+> flush(stderr()); flush(stdout())
+>
+> ### Name: CauchyParameter-class
+> ### Title: Class "CauchyParameter"
+> ### Aliases: CauchyParameter-class initialize,CauchyParameter-method
+> ### Keywords: distribution
+>
+> ### ** Examples
+>
+> W <- new("CauchyParameter",location=1,scale=1)
+> location(W) # location of this distribution is 1.
+[1] 1
+> location(W) <- 2 # location of this distribution is now 2.
+>
+>
+>
+> cleanEx()
+> nameEx("Chisq-class")
+> ### * Chisq-class
+>
+> flush(stderr()); flush(stdout())
+>
+> ### Name: Chisq-class
+> ### Title: Class "Chisq"
+> ### Aliases: Chisq-class Chisq initialize,Chisq-method
+> ### Keywords: distribution
+>
+> ### ** Examples
+>
+> C <- Chisq(df = 1, ncp = 1) # C is a chi-squared distribution with df=1 and ncp=1.
+> r(C)(1) # one random number generated from this distribution, e.g. 0.2557184
+[1] 3.052466
+> d(C)(1) # Density of this distribution is 0.2264666 for x = 1.
+[1] 0.2264666
+> p(C)(1) # Probability that x < 1 is 0.4772499.
+[1] 0.4772499
+> q(C)(.1) # Probability that x < 0.04270125 is 0.1.
+[1] 0.04270125
+> ## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
+> df(C) # df of this distribution is 1.
+[1] 1
+> df(C) <- 2 # df of this distribution is now 2.
+> is(C, "Gammad") # no
+[1] FALSE
+> C0 <- Chisq() # default: Chisq(df=1,ncp=0)
+> is(C0, "Gammad") # yes
+[1] TRUE
+> as(C0,"Gammad")
+Distribution Object of Class: Gammad
+ shape: 0.5
+ scale: 2
+>
+>
+>
+> cleanEx()
+> nameEx("ChisqParameter-class")
+> ### * ChisqParameter-class
+>
+> flush(stderr()); flush(stdout())
+>
+> ### Name: ChisqParameter-class
+> ### Title: Class "ChisqParameter"
+> ### Aliases: ChisqParameter-class initialize,ChisqParameter-method
+> ### Keywords: distribution
+>
+> ### ** Examples
+>
+> W <- new("ChisqParameter",df=1,ncp=1)
+> ncp(W) # ncp of this distribution is 1.
+[1] 1
+> ncp(W) <- 2 # ncp of this distribution is now 2.
+>
+>
+>
+> cleanEx()
+> nameEx("CompoundDistribution-class")
+> ### * CompoundDistribution-class
+>
+> flush(stderr()); flush(stdout())
+>
+> ### Name: CompoundDistribution-class
+> ### Title: Class "CompoundDistribution"
+> ### Aliases: CompoundDistribution-class NumbOfSummandsDistr SummandsDistr
+> ### NumbOfSummandsDistr-methods SummandsDistr-methods
+> ### NumbOfSummandsDistr,CompoundDistribution-method
+> ### SummandsDistr,CompoundDistribution-method
+> ### coerce,CompoundDistribution,UnivarLebDecDistribution-method
+> ### UnivDistrListOrDistribution-class
+> ### Keywords: distribution
+>
+> ### ** Examples
+>
+> CP <- CompoundDistribution(Pois(),Norm())
+> CP
+An object of class "CompoundDistribution"
+
+ The frequency distribution is:
+Distribution Object of Class: Pois
+lambda: 1
+ The summands distribution is/are:
+Distribution Object of Class: Norm
+mean: 0
+sd: 1
+
+This Distribution is:
+An object of class "UnivarLebDecDistribution"
+--- a Lebesgue decomposed distribution:
+
+ Its discrete part (with weight 0.368000) is a
+Distribution Object of Class: Dirac
+location: 0
+This part is accessible with 'discretePart(<obj>)'.
+
+ Its absolutely continuous part (with weight 0.632000) is a
+Distribution Object of Class: AbscontDistribution
+This part is accessible with 'acPart(<obj>)'.
+Warning in (new("standardGeneric", .Data = function (object) :
+ arithmetics on distributions are understood as operations on r.v.'s
+see 'distrARITH()'; for switching off this warning see '?distroptions'
+> p(CP)(0.3)
+[1] 0.7480891
+> plot(CP)
+>
+>
+>
+> cleanEx()
+> nameEx("CompoundDistribution")
+> ### * CompoundDistribution
+>
+> flush(stderr()); flush(stdout())
+>
+> ### Name: CompoundDistribution
+> ### Title: Generating function for Class "CompoundDistribution"
+> ### Aliases: CompoundDistribution
+> ### Keywords: distribution list
+>
+> ### ** Examples
+>
+> CP0 <- CompoundDistribution(Pois(), Norm())
+> CP0
+An object of class "CompoundDistribution"
+
+ The frequency distribution is:
+Distribution Object of Class: Pois
+lambda: 1
+ The summands distribution is/are:
+Distribution Object of Class: Norm
+mean: 0
+sd: 1
+
+This Distribution is:
+An object of class "UnivarLebDecDistribution"
+--- a Lebesgue decomposed distribution:
+
+ Its discrete part (with weight 0.368000) is a
+Distribution Object of Class: Dirac
+location: 0
+This part is accessible with 'discretePart(<obj>)'.
+
+ Its absolutely continuous part (with weight 0.632000) is a
+Distribution Object of Class: AbscontDistribution
+This part is accessible with 'acPart(<obj>)'.
+Warning in (new("standardGeneric", .Data = function (object) :
+ arithmetics on distributions are understood as operations on r.v.'s
+see 'distrARITH()'; for switching off this warning see '?distroptions'
+> CP1 <- CompoundDistribution(DiscreteDistribution(supp = c(1,5,9,11),
++ prob = dbinom(0:3, size = 3,prob = 0.3)),Norm())
+> CP1
+An object of class "CompoundDistribution"
+
+ The frequency distribution is:
+Distribution Object of Class: DiscreteDistribution
+ The summands distribution is/are:
+Distribution Object of Class: Norm
+mean: 0
+sd: 1
+
+This Distribution is:
+Distribution Object of Class: AbscontDistribution
+Warning in (new("standardGeneric", .Data = function (object) :
+ arithmetics on distributions are understood as operations on r.v.'s
+see 'distrARITH()'; for switching off this warning see '?distroptions'
+> UL <- UnivarDistrList(Norm(), Binom(10,0.3), Chisq(df=4), Norm(),
++ Binom(10,0.3), Chisq(df=4), Norm(), Binom(10,0.3),
++ Chisq(df=4), Td(5), Td(10))
+> CP2 <- CompoundDistribution(DiscreteDistribution(supp = c(1,5,9,11),
++ prob = dbinom(0:3, size = 3, prob = 0.3)),UL)
+> plot(CP2)
+>
+>
+>
+> cleanEx()
+> nameEx("ConvPow")
+> ### * ConvPow
+>
+> flush(stderr()); flush(stdout())
+>
+> ### Name: convpow-methods
+> ### Title: Distribution of the sum of univariate i.i.d r.v's
+> ### Aliases: convpow convpow-methods convpow,AcDcLcDistribution-method
+> ### convpow,AbscontDistribution-method convpow,LatticeDistribution-method
+> ### convpow,DiscreteDistribution-method convpow,AcDcLcDistribution-method
+> ### convpow,Norm-method convpow,Binom-method convpow,Nbinom-method
+> ### convpow,ExpOrGammaOrChisq-method convpow,Cauchy-method
+> ### convpow,Pois-method convpow,Dirac-method
+> ### Keywords: distribution
+>
+> ### ** Examples
+>
+> convpow(Exp()+Pois(),4)
+Distribution Object of Class: AbscontDistribution
+Warning in (new("standardGeneric", .Data = function (object) :
+ arithmetics on distributions are understood as operations on r.v.'s
+see 'distrARITH()'; for switching off this warning see '?distroptions'
+>
+>
+>
+> cleanEx()
+> nameEx("DExp-class")
+> ### * DExp-class
+>
+> flush(stderr()); flush(stdout())
+>
+> ### Name: DExp-class
+> ### Title: Class "DExp"
+> ### Aliases: DExp-class DExp Laplace DoubleExponential
+> ### initialize,DExp-method
+> ### Keywords: distribution
+>
+> ### ** Examples
+>
+> D <- DExp(rate = 1) # D is a Laplace distribution with rate = 1.
[TRUNCATED]
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