[Distr-commits] r1075 - pkg/distr/tests/Examples

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Sun Nov 8 18:52:14 CET 2015


Author: stamats
Date: 2015-11-08 18:52:14 +0100 (Sun, 08 Nov 2015)
New Revision: 1075

Modified:
   pkg/distr/tests/Examples/distr-Ex.Rout.save
Log:
update of Rout.save

Modified: pkg/distr/tests/Examples/distr-Ex.Rout.save
===================================================================
--- pkg/distr/tests/Examples/distr-Ex.Rout.save	2015-11-08 14:28:30 UTC (rev 1074)
+++ pkg/distr/tests/Examples/distr-Ex.Rout.save	2015-11-08 17:52:14 UTC (rev 1075)
@@ -1,2835 +1,2835 @@
-
-R Under development (unstable) (2015-05-02 r68310) -- "Unsuffered Consequences"
-Copyright (C) 2015 The R Foundation for Statistical Computing
-Platform: x86_64-unknown-linux-gnu (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)
-> library('distr')
-Loading required package: startupmsg
-:startupmsg>  Utilities for Start-Up Messages (version 0.9.1)
-:startupmsg> 
-:startupmsg>  For more information see ?"startupmsg",
-:startupmsg>  NEWS("startupmsg")
-
-Loading required package: sfsmisc
-Loading required package: SweaveListingUtils
-:SweaveListingUtils>  Utilities for Sweave Together with
-:SweaveListingUtils>  TeX 'listings' Package (version
-:SweaveListingUtils>  0.7)
-:SweaveListingUtils> 
-:SweaveListingUtils>  NOTE: Support for this package
-:SweaveListingUtils>  will stop soon.
-:SweaveListingUtils> 
-:SweaveListingUtils>  Package 'knitr' is providing the
-:SweaveListingUtils>  same functionality in a better
-:SweaveListingUtils>  way.
-:SweaveListingUtils> 
-:SweaveListingUtils>  Some functions from package 'base'
-:SweaveListingUtils>  are intentionally masked ---see
-:SweaveListingUtils>  SweaveListingMASK().
-:SweaveListingUtils> 
-:SweaveListingUtils>  Note that global options are
-:SweaveListingUtils>  controlled by
-:SweaveListingUtils>  SweaveListingoptions() ---c.f.
-:SweaveListingUtils>  ?"SweaveListingoptions".
-:SweaveListingUtils> 
-:SweaveListingUtils>  For more information see
-:SweaveListingUtils>  ?"SweaveListingUtils",
-:SweaveListingUtils>  NEWS("SweaveListingUtils")
-:SweaveListingUtils>  There is a vignette to this
-:SweaveListingUtils>  package; try
-:SweaveListingUtils>  vignette("ExampleSweaveListingUtils").
-
-
-Attaching package: ‘SweaveListingUtils’
-
-The following objects are masked from ‘package:base’:
-
-    library, require
-
-:distr>  Object Oriented Implementation of Distributions (version
-:distr>  2.6)
-: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')
-> cleanEx()
-> nameEx("0distr-package")
-> ### * 0distr-package
-> 
-> flush(stderr()); flush(stdout())
-> 
-> ### Name: distr-package
-> ### Title: distr - object orientated 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
-> 
-> 
-> 
-> 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
-> 
-> 
-> 
-> 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] 0.7344913
-> 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
-> 
-> 
-> 
-> 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
-> 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
-> 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
-> 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 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] 0.7436411
-> 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 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 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 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.
-> r(D)(1) # one random number generated from this distribution, e.g. 0.4190765
-[1] -1.181643
-> d(D)(1) # Density of this distribution is 0.1839397 for x = 1.
-[1] 0.1839397
-> p(D)(1) # Probability that x < 1 is 0.8160603.
-[1] 0.8160603
-> q(D)(.1) # Probability that x < -1.609438 is 0.1.
-[1] -1.609438
-> rate(D) # rate of this distribution is 1.
-[1] 1
-> rate(D) <- 2 # rate of this distribution is now 2.
-> 3*D ###  still a DExp -distribution
-Distribution Object of Class: DExp
- rate: 0.666666666666667
-Warning in function (object)  :
-  arithmetics on distributions are understood as operations on r.v.'s
-see 'distrARITH()'; for switching off this warning see '?distroptions'
-> 
-> 
-> 
-> cleanEx()
-> nameEx("Dirac-class")
-> ### * Dirac-class
-> 
-> flush(stderr()); flush(stdout())
-> 
-> ### Name: Dirac-class
-> ### Title: Class "Dirac"
-> ### Aliases: Dirac-class Dirac initialize,Dirac-method log,Dirac-method
-> ###   Math,Dirac-method
-> ### Keywords: distribution
-> 
-> ### ** Examples
-> 
-> D <- Dirac(location = 0) # D is a Dirac distribution with location=0.
-> r(D)(1)
-[1] 0
-> # r(D)(1) generates a pseudo-random-number according to a Dirac
-> # distribution with location = 0,
-> # which of course will take 0 as value almost surely.
-> d(D)(0) # Density of this distribution is 1 for x = 0.
-[1] 1
-> p(D)(1) # Probability that x < 1 is 1.
-[1] 1
-> q(D)(.1) # q(D)(x) is always 0 (= location).
-[1] 0
-> location(D) # location of this distribution is 0.
-[1] 0
-> location(D) <- 2 # location of this distribution is now 2.
-> 
-> 
-> 
-> cleanEx()
-> nameEx("DiracParameter-class")
-> ### * DiracParameter-class
-> 
-> flush(stderr()); flush(stdout())
-> 
-> ### Name: DiracParameter-class
-> ### Title: Class "DiracParameter"
-> ### Aliases: DiracParameter-class initialize,DiracParameter-method
-> ### Keywords: distribution
-> 
-> ### ** Examples
-> 
-> W <- new("DiracParameter",location=1)
-> location(W) # location of this distribution is 1.
-[1] 1
-> location(W) <- 2 # location of this distribution is now 2.
-> 
-> 
-> 
-> cleanEx()
-> nameEx("DiscreteDistribution-class")
-> ### * DiscreteDistribution-class
-> 
-> flush(stderr()); flush(stdout())
-> 
-> ### Name: DiscreteDistribution-class
-> ### Title: Class "DiscreteDistribution"
-> ### Aliases: DiscreteDistribution-class AffLinDiscreteDistribution-class
-> ###   initialize,DiscreteDistribution-method
-> ###   initialize,AffLinDiscreteDistribution-method
-> ###   sqrt,DiscreteDistribution-method
-> ###   coerce,DiscreteDistribution,LatticeDistribution-method
-> ###   coerce,AffLinDiscreteDistribution,LatticeDistribution-method
-> ### Keywords: distribution
-> 
-> ### ** Examples
-> 
-> # Dirac-measure at 0
-> D1 <- DiscreteDistribution(supp = 0)
-> support(D1)
-[1] 0
-> 
-> # simple discrete distribution
-> D2 <- DiscreteDistribution(supp = c(1:5), prob = c(0.1, 0.2, 0.3, 0.2, 0.2))
-> plot(D2)
-> (pp <- p(D2)(support(D2)))
-[1] 0.1 0.3 0.6 0.8 1.0
-> p(D2)(support(D2)-1e-5)
-[1] 0.0 0.1 0.3 0.6 0.8
-> p(D2)(support(D2)+1e-5)
-[1] 0.1 0.3 0.6 0.8 1.0
-> p.l(D2)(support(D2))
-[1] 0.0 0.1 0.3 0.6 0.8
-> p.l(D2)(support(D2)-1e-5)
-[1] 0.0 0.1 0.3 0.6 0.8
-> p.l(D2)(support(D2)+1e-5)
-[1] 0.1 0.3 0.6 0.8 1.0
-> q(D2)(pp)
-[1] 1 2 3 4 5
-> q(D2)(pp-1e-5)
-[1] 1 2 3 4 5
-> q(D2)(pp+1e-5)
-Warning in q(D2)(pp + 1e-05) : q method of D2 produced NaN's 
-[1]   2   3   4   5 NaN
-> q.r(D2)(pp)
-[1] 2 3 4 5 5
-> q.r(D2)(pp-1e-5)
-[1] 1 2 3 4 5
-> q.r(D2)(pp+1e-5)
-Warning in q.r(D2)(pp + 1e-05) : NaN's produced
-[1]   2   3   4   5 NaN
-> 
-> 
-> 
-> cleanEx()
-> nameEx("DiscreteDistribution")
-> ### * DiscreteDistribution
-> 
-> flush(stderr()); flush(stdout())
-> 
-> ### Name: DiscreteDistribution
-> ### Title: Generating function "DiscreteDistribution"
-> ### Aliases: DiscreteDistribution
-> ### Keywords: distribution
-> 
-> ### ** Examples
-> 
-> # Dirac-measure at 0
-> D1 <- DiscreteDistribution(supp = 0)
-> D1
-Distribution Object of Class: DiscreteDistribution
-> # simple discrete distribution
-> D2 <- DiscreteDistribution(supp = c(1:5), prob = c(0.1, 0.2, 0.3, 0.2, 0.2))
-> D2
[TRUNCATED]

To get the complete diff run:
    svnlook diff /svnroot/distr -r 1075


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