[Vinecopula-commits] r63 - in pkg: . inst tests
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Mi Mär 26 16:18:54 CET 2014
Author: etobi
Date: 2014-03-26 16:18:51 +0100 (Wed, 26 Mar 2014)
New Revision: 63
Modified:
pkg/DESCRIPTION
pkg/inst/ChangeLog
pkg/tests/additonalExampleRuns.R
pkg/tests/additonalExampleRuns.Rout.save
Log:
maintainer changed
Modified: pkg/DESCRIPTION
===================================================================
--- pkg/DESCRIPTION 2014-03-21 10:32:18 UTC (rev 62)
+++ pkg/DESCRIPTION 2014-03-26 15:18:51 UTC (rev 63)
@@ -1,10 +1,10 @@
Package: VineCopula
Type: Package
Title: Statistical inference of vine copulas
-Version: 1.2-1
-Date: 2014-03-21
+Version: 1.3
+Date: 2014-03-26
Author: Ulf Schepsmeier, Jakob Stoeber, Eike Christian Brechmann, Benedikt Graeler
-Maintainer: Ulf Schepsmeier <schepsmeier at ma.tum.de>
+Maintainer: Tobias Erhardt <tobias.erhardt at tum.de>
Depends: R (>= 2.11.0)
Imports: MASS, mvtnorm, igraph, methods, copula
Suggests: CDVine, TSP, ADGofTest
Modified: pkg/inst/ChangeLog
===================================================================
--- pkg/inst/ChangeLog 2014-03-21 10:32:18 UTC (rev 62)
+++ pkg/inst/ChangeLog 2014-03-26 15:18:51 UTC (rev 63)
@@ -2,7 +2,12 @@
Current authors: Ulf Schepsmeier, Tobias Erhardt and Benedikt Graeler
Former authors: Eike Brechmann and Jakob Stoeber
+Maintainer: Tobias Erhardt <tobias.erhardt at tum.de>
+Version 1.3 (March 26, 2014)
+
+- Maintainer changed from Ulf Schepsmeier to Tobias Erhardt (tobias.erhardt at tum.de)
+
Version 1.2-1 (March 21, 2014)
- Moved copula from depends to the more appropriate import field
Modified: pkg/tests/additonalExampleRuns.R
===================================================================
--- pkg/tests/additonalExampleRuns.R 2014-03-21 10:32:18 UTC (rev 62)
+++ pkg/tests/additonalExampleRuns.R 2014-03-26 15:18:51 UTC (rev 63)
@@ -1,3 +1,8 @@
+## switch for testing the following time consuming examples
+docheck <- FALSE
+
+if(docheck){
+
## tests from excluded examples
library(VineCopula)
@@ -220,4 +225,6 @@
set.seed(666)
rCopula(500,vine)
-# End(Not run)
\ No newline at end of file
+# End(Not run)
+
+}
\ No newline at end of file
Modified: pkg/tests/additonalExampleRuns.Rout.save
===================================================================
--- pkg/tests/additonalExampleRuns.Rout.save 2014-03-21 10:32:18 UTC (rev 62)
+++ pkg/tests/additonalExampleRuns.Rout.save 2014-03-26 15:18:51 UTC (rev 63)
@@ -1,5 +1,5 @@
-R version 3.1.0 alpha (2014-03-13 r65184) -- "Unsuffered Consequences"
+R version 3.0.3 (2014-03-06) -- "Warm Puppy"
Copyright (C) 2014 The R Foundation for Statistical Computing
Platform: x86_64-w64-mingw32/x64 (64-bit)
@@ -15,842 +15,754 @@
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
-> ## tests from excluded examples
-> library(VineCopula)
->
-> ## Not run:
-> # chi-plots for bivariate Gaussian copula data
-> n = 500
-> tau = 0.5
->
-> # simulate copula data
-> fam = 1
-> theta = BiCopTau2Par(fam,tau)
-> set.seed(666)
-> dat = BiCopSim(n,fam,theta)
->
-> # create chi-plots
-> par(mfrow=c(1,3))
-> BiCopChiPlot(dat[,1],dat[,2],xlim=c(-1,1),ylim=c(-1,1),
-+ main="General chi-plot")
-> BiCopChiPlot(dat[,1],dat[,2],mode="lower",xlim=c(-1,1),
-+ ylim=c(-1,1),main="Lower chi-plot")
-> BiCopChiPlot(dat[,1],dat[,2],mode="upper",xlim=c(-1,1),
-+ ylim=c(-1,1),main="Upper chi-plot")
->
-> # simulate from a bivariate Clayton copula
-> set.seed(666)
-> simdata = BiCopSim(300,3,2)
-> u1 = simdata[,1]
-> u2 = simdata[,2]
->
-> # perform White's goodness-of-fit test for the true copula
-> BiCopGofTest(u1,u2,family=3)
-$p.value
- [,1]
-[1,] 0.4394173
-
-$statistic
- [,1]
-[1,] 0.5978035
-
->
-> # perform Kendall's goodness-of-fit test for the Frank copula
-> BiCopGofTest(u1,u2,family=5)
-$p.value
- [,1]
-[1,] 0.2979448
-
-$statistic
- [,1]
-[1,] 1.08337
-
->
-> # perform Kendall's goodness-of-fit test for the true copula
-> gof = BiCopGofTest(u1,u2,family=3,method="kendall")
-> gof$p.value.CvM
-[1] 0.46
-> gof$p.value.KS
-[1] 0.39
->
-> # perform Kendall's goodness-of-fit test for the Frank copula
-> gof = BiCopGofTest(u1,u2,family=5,method="kendall")
-> gof$p.value.CvM
-[1] 0
-> gof$p.value.KS
-[1] 0
->
-> # Not run:
-> # Gaussian and Clayton copulas
-> n = 500
-> tau = 0.5
->
-> # simulate from Gaussian copula
-> fam1 = 1
-> theta1 = BiCopTau2Par(fam1,tau)
-> set.seed(666)
-> dat1 = BiCopSim(n,fam1,theta1)
->
-> # simulate from Clayton copula
-> fam2 = 3
-> theta2 = BiCopTau2Par(fam2,tau)
-> set.seed(666)
-> dat2 = BiCopSim(n,fam2,theta2)
->
-> # create K-plots
-> par(mfrow=c(1,2))
-> BiCopKPlot(dat1[,1],dat1[,2],main="Gaussian copula")
-> BiCopKPlot(dat2[,1],dat2[,2],main="Clayton copula")
-> # End(Not run)
->
-> # Not run:
-> # Clayton and rotated Clayton copulas
-> n = 1000
-> tau = 0.5
->
-> # simulate from Clayton copula
-> fam = 3
-> theta = BiCopTau2Par(fam,tau)
-> set.seed(666)
-> dat = BiCopSim(n,fam,theta)
->
-> # create lambda-function plots
-> par(mfrow=c(1,3))
-> BiCopLambda(dat[,1],dat[,2]) # empirical lambda-function
-> BiCopLambda(family=fam,par=theta) # theoretical lambda-function
-> BiCopLambda(dat[,1],dat[,2],family=fam,par=theta) # both
->
-> # simulate from rotated Clayton copula (90 degrees)
-> fam = 23
-> theta = BiCopTau2Par(fam,-tau)
-> set.seed(666)
-> dat = BiCopSim(n,fam,theta)
->
-> # rotate the data to standard Clayton copula data
-> rot_dat = 1-dat[,1]
->
-> par(mfrow=c(1,3))
-> BiCopLambda(rot_dat,dat[,2]) # empirical lambda-function
-> BiCopLambda(family=3,par=-theta) # theoretical lambda-function
-> BiCopLambda(rot_dat,dat[,2],family=3,par=-theta) # both
-> # End(Not run)
->
-> # Not run:
-> ## Example 3: empirical data
-> data(daxreturns)
-> cop3 = BiCopSelect(daxreturns[,1],daxreturns[,4],
-+ familyset=c(1:10,13,14,16,23,24,26))
-> cop3$family
-[1] 14
-> cop3$par
-[1] 1.614805
-> cop3$par2
-[1] 0
-> # End(Not run)
->
-> # Not run:
-> # simulate from a t-copula
-> set.seed(666)
-> dat = BiCopSim(500,2,0.7,5)
->
-> # apply the test for families 1-10
-> vcgof = BiCopVuongClarke(dat[,1],dat[,2],familyset=c(1:10))
->
-> # display the Vuong test scores
-> vcgof[1,]
- 1 2 3 4 5 6 7 8 9 10
- 0 7 -3 0 -2 -8 7 -2 7 -6
-> # End(Not run)
->
-> # Not run:
-> # select the R-vine structure, families and parameters
-> RVM = RVineStructureSelect(daxreturns[,1:5],c(1:6))
-> RVM$Matrix
- [,1] [,2] [,3] [,4] [,5]
-[1,] 3 0 0 0 0
-[2,] 4 2 0 0 0
-[3,] 5 4 1 0 0
-[4,] 1 5 4 5 0
-[5,] 2 1 5 4 4
-> RVM$par
- [,1] [,2] [,3] [,4] [,5]
-[1,] 0.0000000 0.0000000 0.0000000 0.000000 0
-[2,] 0.4144800 0.0000000 0.0000000 0.000000 0
-[3,] 0.6292681 0.8673638 0.0000000 0.000000 0
-[4,] 0.1837189 2.0586327 0.3912384 0.000000 0
-[5,] 0.6149777 0.5934291 0.6183352 0.684548 0
-> RVM$par2
- [,1] [,2] [,3] [,4] [,5]
-[1,] 0.000000 0.000000 0.000000 0.000000 0
-[2,] 0.000000 0.000000 0.000000 0.000000 0
-[3,] 0.000000 0.000000 0.000000 0.000000 0
-[4,] 10.184146 0.000000 0.000000 0.000000 0
-[5,] 4.634146 4.601458 6.502828 8.766498 0
->
-> # select the C-vine structure, families and parameters
-> CVM = RVineStructureSelect(daxreturns[,1:5],c(1:6),type="CVine")
-> CVM$Matrix
- [,1] [,2] [,3] [,4] [,5]
-[1,] 3 0 0 0 0
-[2,] 4 1 0 0 0
-[3,] 1 4 2 0 0
-[4,] 2 2 4 5 0
-[5,] 5 5 5 4 4
-> CVM$par
- [,1] [,2] [,3] [,4] [,5]
-[1,] 0.0000000 0.0000000 0.000000 0.000000 0
-[2,] 0.4551787 0.0000000 0.000000 0.000000 0
-[3,] 0.8908653 1.3220209 0.000000 0.000000 0
-[4,] 0.4917446 0.3834983 1.522463 0.000000 0
-[5,] 0.4521326 0.6183352 0.564711 0.684548 0
-> CVM$par2
- [,1] [,2] [,3] [,4] [,5]
-[1,] 0.000000 0.000000 0.000000 0.000000 0
-[2,] 0.000000 0.000000 0.000000 0.000000 0
-[3,] 0.000000 0.000000 0.000000 0.000000 0
-[4,] 8.054474 6.557946 0.000000 0.000000 0
-[5,] 5.707574 6.502828 5.539292 8.766498 0
->
-> # compare the two models based on the data
-> clarke = RVineClarkeTest(daxreturns[,1:5],RVM,CVM)
-> clarke$statistic
-[1] 539
-> clarke$statistic.Schwarz
-[1] 548
-> clarke$p.value
-[1] 0.02021913
-> clarke$p.value.Schwarz
-[1] 0.07299638
-> # End(Not run)
->
-> # Not run:
-> # White test with asymptotic p-value
-> RVineGofTest(daxreturns[,1:5], RVM, B=0)
-$White
-[1] 150.4045
-
-$p.value
-[1] 0.03144801
-
->
-> # ECP2 test with Cramer-von-Mises test statistic and a bootstrap with 200 replications
-> # for the calculation of the p-value
-> RVineGofTest(daxreturns[,1:5], RVM, method="ECP2", statistic="CvM", B=200)
-$CvM
-[1] 0.09003453
-
-$p.value
-[1] 0.775
-
-> # End(Not run)
->
-> ## Not run:
-> # define 5-dimensional R-vine tree structure matrix
-> Matrix = c(5,2,3,1,4,0,2,3,4,1,0,0,3,4,1,0,0,0,4,1,0,0,0,0,1)
-> Matrix = matrix(Matrix,5,5)
->
-> # define R-vine pair-copula family matrix
-> family = c(0,1,3,4,4,0,0,3,4,1,0,0,0,4,1,0,0,0,0,3,0,0,0,0,0)
-> family = matrix(family,5,5)
->
-> # define R-vine pair-copula parameter matrix
-> par = c(0,0.2,0.9,1.5,3.9,0,0,1.1,1.6,0.9,0,0,0,1.9,0.5,
-+ 0,0,0,0,4.8,0,0,0,0,0)
-> par = matrix(par,5,5)
->
-> # define second R-vine pair-copula parameter matrix
-> par2 = matrix(0,5,5)
->
-> # define RVineMatrix object
-> RVM = RVineMatrix(Matrix=Matrix,family=family,par=par,par2=par2,
-+ names=c("V1","V2","V3","V4","V5"))
->
-> # simulate a sample of size 300 from the R-vine copula model
-> set.seed(666)
-> simdata = RVineSim(300,RVM)
->
-> # compute the MLE
-> mle = RVineMLE(simdata,RVM,grad=TRUE)
-iter 10 value -1111.253373
-iter 20 value -1111.562935
-iter 30 value -1111.991155
-iter 40 value -1112.008869
-iter 50 value -1112.062737
-iter 60 value -1112.114981
-iter 70 value -1112.168354
-final value -1112.174829
-converged
-> mle$RVM
-R-vine matrix:
- [,1] [,2] [,3] [,4] [,5]
-[1,] 5 0 0 0 0
-[2,] 2 2 0 0 0
-[3,] 3 3 3 0 0
-[4,] 1 4 4 4 0
-[5,] 4 1 1 1 1
-
-Where
-1 <-> V1
-2 <-> V2
-3 <-> V3
-4 <-> V4
-5 <-> V5
-> # End(Not run)
->
-> ##TODO shorten this test, takes too long
-> # # Not run:
-> # RVM = RVineStructureSelect(daxreturns,c(1:6),progress=TRUE)
-> # # End(Not run)
-> #
-> # # specify a C-vine copula model with only Clayton, Gumbel and Frank copulas
-> # # Not run:
-> # CVM = RVineStructureSelect(daxreturns,c(3,4,5),"CVine")
-> # # End(Not run)
-> # # determine the order of the nodes in a D-vine using the package TSP
-> # # Not run:
-> # library(TSP)
-> # d = dim(daxreturns)[2]
-> # M = 1 - abs(TauMatrix(daxreturns))
-> # hamilton = insert_dummy(TSP(M),label="cut")
-> # sol = solve_TSP(hamilton,method="repetitive_nn")
-> # order = cut_tour(sol,"cut")
-> # DVM = D2RVine(order,family=rep(0,d*(d-1)/2),par=rep(0,d*(d-1)/2))
-> # RVineCopSelect(daxreturns,c(1:6),DVM$Matrix)
-> # End(Not run)
->
-> # Not run:
-> RVM = RVineStructureSelect(daxreturns[,1:5],c(1:6))
-> CVM = RVineStructureSelect(daxreturns[,1:5],c(1:6),type="CVine")
->
-> # compare the two models based on the data
-> vuong = RVineVuongTest(daxreturns[,1:5],RVM,CVM)
-> vuong$statistic
-[1] 0.6982158
-> vuong$statistic.Schwarz
-[1] 1.027616
-> vuong$p.value
-[1] 0.4850423
-> vuong$p.value.Schwarz
-[1] 0.3041306
-> # End(Not run)
->
-> # Not run:
-> library(copula)
-
-Attaching package: 'copula'
-
-The following object is masked from 'package:VineCopula':
-
- fitCopula
-
-> vine <- vineCopula(4L,"CVine")
->
-> set.seed(666)
-> rCopula(500,vine)
- [,1] [,2] [,3] [,4]
- [1,] 0.7743684903 0.197224191 0.9780138442 0.201327350
- [2,] 0.3612444273 0.742611942 0.9787284394 0.498113709
- [3,] 0.0133158357 0.259946129 0.7758930807 0.016379053
- [4,] 0.0957447842 0.142163540 0.2111262376 0.811256444
- [5,] 0.0365471959 0.891637413 0.4832364111 0.466664528
- [6,] 0.9842240803 0.601345547 0.0383443474 0.141495691
- [7,] 0.8063855253 0.266685676 0.0427020509 0.612174522
- [8,] 0.5533483981 0.853500765 0.4697785398 0.397616561
- [9,] 0.8046367336 0.508897385 0.6349153537 0.494251721
- [10,] 0.2801308988 0.908710354 0.7841161578 0.558997022
- [11,] 0.2444374892 0.530970655 0.1183959420 0.983383433
- [12,] 0.8977528436 0.738573763 0.3773106968 0.606168831
- [13,] 0.5121942617 0.989246660 0.0691335856 0.084620626
- [14,] 0.1299455715 0.746132021 0.0388791817 0.685635417
- [15,] 0.1439773615 0.891079958 0.0896361163 0.037732719
- [16,] 0.7748743587 0.812063878 0.2606025457 0.651594998
- [17,] 0.9238038510 0.266106121 0.2661329871 0.910917896
- [18,] 0.5905635331 0.918147645 0.6037942769 0.328263949
- [19,] 0.6661178111 0.874787498 0.0688752665 0.793463009
- [20,] 0.5714270058 0.048944066 0.9803513540 0.914537349
- [21,] 0.7659584857 0.775846373 0.3125150499 0.842217308
- [22,] 0.3141499059 0.756563893 0.9675243802 0.169422925
- [23,] 0.6968751778 0.872650789 0.1324707782 0.078513110
- [24,] 0.3782238525 0.579624758 0.5364251249 0.108531924
- [25,] 0.7403151453 0.451789635 0.6461082133 0.749298733
- [26,] 0.5782921447 0.369409172 0.8813395619 0.599252820
- [27,] 0.2417592837 0.991064092 0.2720299934 0.225755411
- [28,] 0.3065364894 0.736066050 0.2058734051 0.242183074
- [29,] 0.4066693399 0.411321262 0.2207378661 0.868450051
- [30,] 0.7642357713 0.217509840 0.8997187309 0.816142634
- [31,] 0.1601893809 0.566658863 0.1824444511 0.867856246
- [32,] 0.0937132754 0.638223762 0.9734738106 0.009292930
- [33,] 0.7511339965 0.103923442 0.3436669305 0.591091853
- [34,] 0.5735987651 0.951237907 0.6553645076 0.377351639
- [35,] 0.9499114281 0.578954988 0.4752220884 0.254485867
- [36,] 0.3758446192 0.052798728 0.4420929269 0.697271063
- [37,] 0.7591612791 0.113734436 0.5760056155 0.099177053
- [38,] 0.1097460489 0.089127219 0.4737118890 0.356403576
- [39,] 0.2159698724 0.573215632 0.0016242201 0.718207759
- [40,] 0.2651135898 0.153830340 0.2900760283 0.067229538
- [41,] 0.9318368479 0.133479226 0.8126322976 0.759258038
- [42,] 0.3713044880 0.952166667 0.0996854173 0.307502680
- [43,] 0.4942615442 0.799964843 0.8426329251 0.647393905
- [44,] 0.6565674008 0.228435223 0.9240007692 0.485242063
- [45,] 0.5546194194 0.852844047 0.0898779368 0.740950904
- [46,] 0.3131348765 0.100732039 0.1840703834 0.213704721
- [47,] 0.6256980768 0.428000274 0.6235166367 0.577644360
- [48,] 0.1489856443 0.575752754 0.6500458319 0.638607423
- [49,] 0.7874355474 0.080619973 0.2898914691 0.223104578
- [50,] 0.5703688168 0.256050143 0.5171432674 0.769378419
- [51,] 0.1717156325 0.339101385 0.0346307140 0.378165489
- [52,] 0.9764601048 0.628306977 0.7929682066 0.576068396
- [53,] 0.1587420395 0.375621754 0.7126429004 0.642280536
- [54,] 0.2176803409 0.835219718 0.7511949919 0.092663403
- [55,] 0.1462978539 0.224104125 0.2406677336 0.479203157
- [56,] 0.1708911972 0.593215867 0.4259613717 0.782201018
- [57,] 0.8910149985 0.142018785 0.0872662787 0.298543895
- [58,] 0.3779736755 0.310509426 0.8581924702 0.185521572
- [59,] 0.0457103401 0.879344751 0.3266109165 0.610508331
- [60,] 0.4137852436 0.631626930 0.0201767548 0.560452844
- [61,] 0.2195571528 0.718596233 0.8913105952 0.714111986
- [62,] 0.7382447990 0.744075007 0.8478900143 0.701567872
- [63,] 0.4122337785 0.671587694 0.8733269582 0.958611961
- [64,] 0.6021437587 0.955820256 0.3093991736 0.610134651
- [65,] 0.6450917169 0.928400521 0.1264171537 0.114088232
- [66,] 0.7526843124 0.436705104 0.7802989122 0.076146137
- [67,] 0.2997063766 0.654224689 0.1309945930 0.765423296
- [68,] 0.3087085823 0.876935426 0.6371941748 0.342596608
- [69,] 0.4284886608 0.849930797 0.0008197445 0.813576228
- [70,] 0.0874580105 0.289057647 0.8494888905 0.805416501
- [71,] 0.9950445746 0.526671264 0.1112271971 0.945346809
- [72,] 0.7236955145 0.766487946 0.9305669612 0.498757267
- [73,] 0.7239606669 0.361902371 0.1568023660 0.303363824
- [74,] 0.7426302731 0.399672838 0.9347559172 0.946996531
- [75,] 0.5447802225 0.838801894 0.5616297950 0.707813082
- [76,] 0.0706888989 0.119998450 0.0310555075 0.463001627
- [77,] 0.4483564957 0.872894669 0.5048730967 0.902939290
- [78,] 0.0438287666 0.643314284 0.6988559945 0.432357483
- [79,] 0.8284931015 0.841108692 0.9299757103 0.485348572
- [80,] 0.7633930759 0.722670076 0.1641295145 0.992984264
- [81,] 0.4222436752 0.510317259 0.8841753434 0.815883017
- [82,] 0.3102896563 0.290614294 0.9858013957 0.483377530
- [83,] 0.1074008208 0.895984350 0.7338644972 0.764169478
- [84,] 0.0669399693 0.586228112 0.9107325065 0.992980055
- [85,] 0.7499900353 0.032749303 0.2553250678 0.424626995
- [86,] 0.3636265502 0.491994663 0.4343010753 0.570558629
- [87,] 0.9078977865 0.149545077 0.4103580574 0.386177163
- [88,] 0.3463237630 0.180769041 0.2505669079 0.723566933
- [89,] 0.3568387409 0.762676157 0.0026778339 0.902502597
- [90,] 0.9372461650 0.028783082 0.5805151563 0.320475659
- [91,] 0.5341461205 0.844306072 0.0044064738 0.239406295
- [92,] 0.0869177727 0.431421488 0.8170050057 0.685073657
- [93,] 0.5969637693 0.649056442 0.8868091749 0.752216479
- [94,] 0.4407886460 0.765468751 0.6110754195 0.230400142
- [95,] 0.7709763278 0.003451970 0.3045489269 0.677755016
- [96,] 0.8306224118 0.981180732 0.0146101408 0.427443687
- [97,] 0.0260336597 0.497721859 0.7918673381 0.536566794
- [98,] 0.8351932005 0.254128620 0.7913846564 0.873722913
- [99,] 0.2165347089 0.939788748 0.1385002721 0.383461147
-[100,] 0.4339649915 0.296471564 0.7247037594 0.336028221
-[101,] 0.9783641526 0.866081857 0.9018030704 0.325471421
-[102,] 0.3971384598 0.265053156 0.9096906008 0.838811320
-[103,] 0.7162932027 0.695596617 0.4661542471 0.385693899
-[104,] 0.9766215621 0.978381113 0.9296605005 0.850788791
-[105,] 0.8914492358 0.323866647 0.5856527244 0.253404879
-[106,] 0.6137620085 0.517032054 0.7084812184 0.384624342
-[107,] 0.6937829796 0.482504157 0.2806229971 0.111000120
-[108,] 0.2252501699 0.192968889 0.7676781283 0.144796298
-[109,] 0.3975286756 0.856579141 0.7646776433 0.349135153
-[110,] 0.2514651113 0.468221299 0.2596560335 0.251388092
-[111,] 0.1048730048 0.480938709 0.5862234468 0.157663264
-[112,] 0.8533307265 0.802534590 0.0630291228 0.774797393
-[113,] 0.8543458662 0.959840256 0.5253083515 0.794741470
-[114,] 0.9343227027 0.415850785 0.5709062461 0.715303819
-[115,] 0.4945777149 0.319346633 0.4525958812 0.921565412
-[116,] 0.5938526166 0.742607552 0.3950976874 0.381024701
-[117,] 0.7792707451 0.446705242 0.8011080394 0.053082889
-[118,] 0.6759392642 0.110763745 0.5593784570 0.578903007
-[119,] 0.0537102909 0.861216648 0.5484887112 0.191311767
-[120,] 0.1262770237 0.404101574 0.2281427665 0.790996143
-[121,] 0.7423158411 0.264997610 0.0497878187 0.727313877
-[122,] 0.1385788159 0.473839645 0.2715208770 0.361259246
-[123,] 0.3941312041 0.516422224 0.5751485603 0.913428178
-[124,] 0.7122545927 0.282151025 0.7430913700 0.336726994
-[125,] 0.0864723539 0.137007158 0.8332147521 0.281362747
-[126,] 0.3166397884 0.093503658 0.6104916255 0.486205183
-[127,] 0.4951614400 0.621448159 0.2981001402 0.622220361
-[128,] 0.8094501127 0.343012312 0.2104642675 0.773515745
-[129,] 0.9557679957 0.286419369 0.0794727448 0.661053497
-[130,] 0.3118138872 0.630501184 0.6049537384 0.876706274
-[131,] 0.0342228804 0.771673130 0.9368422253 0.254222035
-[132,] 0.3931704909 0.407810160 0.6519637303 0.232840615
-[133,] 0.2398367440 0.463389060 0.0757585869 0.739007716
-[134,] 0.6477067082 0.498322295 0.8434889137 0.425229206
-[135,] 0.2592272202 0.847242712 0.3250673641 0.072640638
-[136,] 0.4135137298 0.294362260 0.0082187485 0.169481597
-[137,] 0.1102090557 0.357150810 0.4791381841 0.628914608
-[138,] 0.0291915040 0.317528534 0.3061793284 0.688495747
-[139,] 0.5546681047 0.777362950 0.7623155026 0.425375876
-[140,] 0.9654694719 0.937939378 0.4363308840 0.365133651
-[141,] 0.9337793922 0.093578767 0.1778323287 0.634321812
-[142,] 0.4263039595 0.247728514 0.6804367560 0.951060107
-[143,] 0.0055627781 0.657620627 0.4659305960 0.862668524
-[144,] 0.1916651884 0.882191312 0.1169548559 0.884029913
-[145,] 0.8443164860 0.545540991 0.3381157848 0.612806927
-[146,] 0.3035845007 0.996642929 0.2449090297 0.494586456
-[147,] 0.0983962484 0.551325806 0.0632993493 0.110916249
-[148,] 0.2652095708 0.659197510 0.1011707778 0.915162335
-[149,] 0.4929900784 0.408335317 0.9016870754 0.628590122
-[150,] 0.0489578447 0.394935755 0.2591228082 0.331622616
-[151,] 0.6669344027 0.625317686 0.5075432686 0.284504177
-[152,] 0.3621549048 0.768481911 0.2988393311 0.371669197
-[153,] 0.0326483354 0.144800921 0.4674971097 0.467041486
-[154,] 0.6198881525 0.996896958 0.9224957055 0.030758351
-[155,] 0.5376262197 0.324835435 0.9192293161 0.362162672
-[156,] 0.2576842806 0.777084367 0.0603294310 0.148089551
-[157,] 0.3500228543 0.724576649 0.1668874554 0.625389982
-[158,] 0.2161285661 0.080344860 0.8572669341 0.534154641
-[159,] 0.9111834818 0.339142072 0.2979932092 0.839897137
-[160,] 0.0560075995 0.251565638 0.1065861024 0.084512484
-[161,] 0.0462357609 0.653913901 0.5670640329 0.604898218
-[162,] 0.3610695442 0.478445034 0.2008723405 0.222925923
-[163,] 0.9494444395 0.030701017 0.4029161467 0.581024964
-[164,] 0.7975459564 0.212698670 0.7370460802 0.834826638
-[165,] 0.3424032438 0.373054494 0.7425395199 0.102290838
-[166,] 0.8210614766 0.719421685 0.9488708046 0.614808284
-[167,] 0.4656176886 0.687057783 0.8464449772 0.275338395
-[168,] 0.2352189699 0.869283458 0.4975102539 0.530897514
-[169,] 0.8449436247 0.231636410 0.0050560117 0.197853174
-[170,] 0.8511695394 0.794882977 0.4079136280 0.341474468
-[171,] 0.2390391729 0.679682165 0.1650999326 0.534640821
-[172,] 0.9170250949 0.708150995 0.7061667675 0.180957641
-[173,] 0.7601360832 0.898726894 0.7251891324 0.194109676
-[174,] 0.7113639880 0.917680320 0.8643603884 0.609830835
-[175,] 0.2820347275 0.971891471 0.5355856742 0.227349275
-[176,] 0.5997360051 0.154081805 0.4637709183 0.845961729
-[177,] 0.4354194493 0.773573316 0.0967188128 0.424934591
-[178,] 0.5771441387 0.475725745 0.1756015311 0.234882956
-[179,] 0.4343538592 0.574824400 0.9920985959 0.756193620
-[180,] 0.3622156528 0.547339699 0.1859536748 0.524521267
-[181,] 0.2250695992 0.911340973 0.7638558464 0.341152911
-[182,] 0.8203911844 0.984728851 0.4024798393 0.398337749
-[183,] 0.3553854842 0.996304989 0.4209121999 0.825072953
-[184,] 0.0540067432 0.126679682 0.9832146429 0.438097001
-[185,] 0.0977464563 0.144636228 0.6997192786 0.964076800
-[186,] 0.5718035589 0.976129007 0.7661929270 0.353297002
-[187,] 0.6672807375 0.812140311 0.6806913668 0.417172965
-[188,] 0.6312760920 0.845643334 0.3147387863 0.623067643
-[189,] 0.2489069414 0.170307136 0.0528473828 0.352397213
-[190,] 0.7154197919 0.769427613 0.0439616535 0.296600588
-[191,] 0.3728102313 0.606454670 0.1744521784 0.325637069
-[192,] 0.5313717655 0.213290896 0.1098954093 0.470625348
-[193,] 0.0183186221 0.612048755 0.3343215247 0.983097545
-[194,] 0.6339995915 0.751820059 0.2734629191 0.243564314
-[195,] 0.3502755684 0.483300012 0.9734322524 0.218934502
-[196,] 0.4920768677 0.722552758 0.5070240900 0.070143877
-[197,] 0.0194451697 0.205571976 0.7541954345 0.630418118
-[198,] 0.8489873135 0.051017051 0.8036233829 0.583407820
-[199,] 0.8866788479 0.950272547 0.0732990042 0.834296813
-[200,] 0.3632328885 0.444549295 0.9541965688 0.010449900
-[201,] 0.2735836152 0.830732305 0.8230200189 0.392719318
-[202,] 0.7352467482 0.901445550 0.0822419475 0.368879102
-[203,] 0.3630899456 0.488129941 0.8006980552 0.575974445
-[204,] 0.7874140171 0.849424730 0.1900799496 0.533960375
-[205,] 0.8334457523 0.754456814 0.4303900155 0.755243090
-[206,] 0.3164512538 0.821538813 0.6494338685 0.154915826
-[207,] 0.3741788722 0.286865845 0.8432514123 0.181860059
-[208,] 0.6069478868 0.657173519 0.8113320200 0.546618887
-[209,] 0.8379858243 0.066471890 0.9748757288 0.805784753
-[210,] 0.0663143010 0.781842248 0.5844962969 0.798303778
-[211,] 0.5553825684 0.826247105 0.2980761654 0.934750434
-[212,] 0.6941594929 0.863456176 0.2019991342 0.263072162
-[213,] 0.8025015295 0.022981469 0.7881118841 0.121721596
-[214,] 0.2573423921 0.105063497 0.3959441814 0.406720767
-[215,] 0.4574301527 0.014828125 0.9075640836 0.366266056
-[216,] 0.7250718824 0.783072366 0.4091000268 0.215065519
-[217,] 0.4007112575 0.590563430 0.5302661911 0.147716149
-[218,] 0.2249917972 0.566724799 0.2234066734 0.054572506
-[219,] 0.6243523695 0.855703998 0.0435405250 0.370553982
-[220,] 0.7651069134 0.951624621 0.4868271784 0.589320412
-[221,] 0.6758246957 0.319414223 0.6893930857 0.536409341
-[222,] 0.1508573301 0.847545645 0.3025167799 0.255791885
-[223,] 0.5158530220 0.665776487 0.5712286504 0.972977022
-[224,] 0.4382174690 0.607895790 0.8810680558 0.382243131
-[225,] 0.9040353345 0.818195505 0.1890957728 0.279341920
-[226,] 0.0956006302 0.433048549 0.1651034511 0.184365910
-[227,] 0.7956483513 0.622831352 0.5386761294 0.034711238
-[228,] 0.3661794967 0.195988555 0.2794191148 0.962412738
-[229,] 0.9471271602 0.549059042 0.9749584261 0.717982193
-[230,] 0.3556773327 0.867656888 0.2311769573 0.076064603
-[231,] 0.3916409630 0.681572748 0.9537506220 0.020585128
-[232,] 0.7171780958 0.669524003 0.6586226965 0.254619111
-[233,] 0.3992693252 0.494142564 0.1740932919 0.194849428
-[234,] 0.8798466546 0.476180211 0.1617385235 0.405467161
-[235,] 0.1666286134 0.075125683 0.2838694500 0.076784107
-[236,] 0.9361824323 0.933077563 0.1356491460 0.679490731
-[237,] 0.5197204188 0.339432430 0.0399253590 0.182384872
-[238,] 0.3721226270 0.752011640 0.1098320589 0.798284948
-[239,] 0.1836079187 0.603453786 0.6101417094 0.041103652
-[240,] 0.4993634163 0.207342210 0.3261762194 0.486902969
-[241,] 0.6467777344 0.129989076 0.6651675196 0.449809124
-[242,] 0.6536722353 0.695856193 0.7535691005 0.061294960
-[243,] 0.0499363518 0.046064124 0.8446276195 0.104884493
-[244,] 0.2620879861 0.148730939 0.1752178846 0.019662158
-[245,] 0.4427078820 0.094287481 0.8933788843 0.585570112
-[246,] 0.9169778530 0.648075843 0.7762387784 0.204912888
-[247,] 0.5732168553 0.863256845 0.5047426480 0.469652176
-[248,] 0.4276488579 0.131531685 0.1593779558 0.845790585
-[249,] 0.8587067372 0.502891751 0.5593184705 0.375858957
-[250,] 0.9890882210 0.938063616 0.9706202168 0.216183099
-[251,] 0.8379715749 0.129972132 0.5695172495 0.625571513
-[252,] 0.7212316899 0.572297784 0.0382156211 0.051894007
-[253,] 0.5216590953 0.015851347 0.9769222983 0.272455045
-[254,] 0.5143919997 0.114772279 0.1596595603 0.809009656
-[255,] 0.7357275770 0.853319851 0.2404850596 0.704516945
-[256,] 0.1952619776 0.944837198 0.3381335489 0.726653310
-[257,] 0.6910012066 0.214935871 0.4175838032 0.218764917
-[258,] 0.4867478984 0.343270314 0.2169513768 0.380788512
-[259,] 0.4428913160 0.343588427 0.5667717615 0.949275269
-[260,] 0.1775206316 0.142845772 0.0695777584 0.118463847
-[261,] 0.2351934593 0.337216868 0.9805003721 0.005284573
-[262,] 0.4857526280 0.558714604 0.5375014008 0.511780816
-[263,] 0.6552407253 0.130329409 0.7706996505 0.282453222
-[264,] 0.2740938128 0.395738140 0.1035083684 0.006252106
-[265,] 0.7483767993 0.547375288 0.6094368612 0.932357808
-[266,] 0.6706526354 0.151936714 0.9280017349 0.642849064
-[267,] 0.1692593219 0.512618867 0.8483696235 0.554460279
-[268,] 0.6046569496 0.175424204 0.5205884210 0.980532835
-[269,] 0.4171814560 0.160848656 0.0254654889 0.898504830
-[270,] 0.4675834295 0.565785344 0.8435611597 0.885702458
-[271,] 0.2869922114 0.653929896 0.0656541944 0.549899117
-[272,] 0.2903471391 0.175998944 0.2433835415 0.855399843
-[273,] 0.9098031069 0.600858136 0.0691988289 0.630983036
-[274,] 0.5219512563 0.196392351 0.9942230587 0.171735779
-[275,] 0.7468491504 0.370164049 0.7109902038 0.282020319
-[276,] 0.1262481522 0.390918806 0.8852912916 0.104233933
-[277,] 0.0300880789 0.647038511 0.1334821235 0.240433870
-[278,] 0.6879101389 0.589410251 0.4775275313 0.491272935
-[279,] 0.6160576248 0.761771664 0.2333714277 0.272765368
-[280,] 0.3549011711 0.051849936 0.8768312477 0.877099060
-[281,] 0.8581745944 0.971428056 0.5737855358 0.332571355
-[282,] 0.0207595848 0.042617511 0.7648429871 0.827382307
-[283,] 0.6349156951 0.124888753 0.7582474155 0.187631488
-[284,] 0.1530019275 0.031149091 0.9507271959 0.772281578
-[285,] 0.6720045879 0.978253266 0.1504266458 0.133118892
-[286,] 0.8485787737 0.734150176 0.8971518457 0.308240966
-[287,] 0.8162173289 0.762108188 0.0482832582 0.678645760
-[288,] 0.1517000652 0.989808477 0.5504770332 0.590718119
-[289,] 0.6345506713 0.545683430 0.0139598753 0.678947515
-[290,] 0.8936809630 0.442411056 0.1092832964 0.419108480
-[291,] 0.9164704378 0.303237157 0.7087321593 0.891897406
-[292,] 0.5595637094 0.593235709 0.8172157183 0.180815238
-[293,] 0.5450307759 0.731739299 0.7757680221 0.936030307
-[294,] 0.9844803826 0.952755239 0.7349386474 0.200063891
-[295,] 0.5252404297 0.912472579 0.1983703848 0.873221091
-[296,] 0.5562255983 0.346838131 0.2333369483 0.126236536
-[297,] 0.4020865897 0.884241141 0.2719432884 0.604082966
-[298,] 0.7625291559 0.952015422 0.6255507688 0.757415980
-[299,] 0.5018466183 0.931425986 0.1910752419 0.806532523
-[300,] 0.2368220380 0.122242337 0.3275852152 0.173029160
-[301,] 0.5842146724 0.936198387 0.8389963040 0.126142483
-[302,] 0.2276427920 0.316277360 0.5839341637 0.590474609
-[303,] 0.5422491468 0.200553625 0.5389597269 0.879883609
-[304,] 0.7374660282 0.768241838 0.9755696333 0.763199614
-[305,] 0.1471564339 0.559007475 0.9607511451 0.217728840
-[306,] 0.5889839104 0.675189323 0.5226181226 0.430570702
-[307,] 0.7506851617 0.386064682 0.4334508299 0.965842676
-[308,] 0.2637242335 0.650240324 0.3104421902 0.638478931
-[309,] 0.1803990712 0.089696390 0.2932914000 0.006119711
-[310,] 0.7184373385 0.404312139 0.1811476685 0.965097900
-[311,] 0.2377872753 0.984447725 0.8718100854 0.106952735
-[312,] 0.3503712702 0.603536791 0.8463436530 0.310144706
-[313,] 0.4495570462 0.272465356 0.5138976437 0.488285378
-[314,] 0.8614247281 0.744840986 0.1210435661 0.716413555
-[315,] 0.1381337575 0.230298426 0.9294903460 0.636520796
-[316,] 0.7497352820 0.403666644 0.8337023426 0.202122381
-[317,] 0.3304093368 0.647110599 0.3845536171 0.331561915
-[318,] 0.9508939169 0.080059566 0.0898211326 0.447491282
-[319,] 0.5857214541 0.141073883 0.1875592161 0.181189312
-[320,] 0.0435665241 0.641066964 0.0711824722 0.029968474
-[321,] 0.8272884621 0.002672554 0.7767159531 0.245260445
-[322,] 0.2731244157 0.085408063 0.2267000161 0.289309197
-[323,] 0.0462573939 0.811523305 0.1565170230 0.912522806
-[324,] 0.2103107716 0.739090083 0.2226596023 0.409184119
-[325,] 0.4961829542 0.965206025 0.6379224574 0.234194163
-[326,] 0.0008594517 0.978437975 0.9299203167 0.034800552
-[327,] 0.0392625227 0.771819892 0.3514823148 0.490745436
-[328,] 0.5656738437 0.684209259 0.3451482116 0.451761807
-[329,] 0.6252417772 0.079320913 0.2755355502 0.746796617
-[330,] 0.2451075327 0.365693996 0.8820323015 0.706722256
-[331,] 0.5734970425 0.119838247 0.1386956216 0.963373072
-[332,] 0.8048224875 0.931301645 0.6412679160 0.307184222
-[333,] 0.2925654361 0.303601390 0.7828756943 0.931845217
-[334,] 0.9969732796 0.564097288 0.8340119412 0.754510663
-[335,] 0.3455017877 0.795235615 0.0569652505 0.611305799
-[336,] 0.2326845648 0.521942220 0.2309741084 0.313772211
-[337,] 0.0869935376 0.723186854 0.8113833682 0.639738104
-[338,] 0.2045802616 0.380672575 0.5373175945 0.716390287
-[339,] 0.6589587668 0.506170188 0.9339784922 0.100771416
-[340,] 0.3214371668 0.473791970 0.2646674979 0.179875074
-[341,] 0.7434530903 0.984879570 0.4664959104 0.117323593
-[342,] 0.4472260750 0.892814937 0.5007153689 0.516901009
-[343,] 0.4599100070 0.204192071 0.5612023761 0.483082423
-[344,] 0.4270402647 0.987336002 0.7972487614 0.112641990
-[345,] 0.4507297378 0.746419842 0.8726341100 0.589500092
-[346,] 0.7132621077 0.550999165 0.0264370556 0.982933392
-[347,] 0.6183664217 0.458623182 0.2545521415 0.384219691
-[348,] 0.5129058261 0.226279549 0.9553426658 0.474686575
-[349,] 0.0139840404 0.377497884 0.3167468484 0.271984325
-[350,] 0.6544892930 0.589097009 0.7383347314 0.967833379
-[351,] 0.2483195239 0.783252000 0.4792166667 0.943698976
-[352,] 0.3341092798 0.376029821 0.5487082228 0.173540368
-[353,] 0.8799060567 0.286639028 0.5109444920 0.647152330
-[354,] 0.3399565150 0.713364316 0.7914584880 0.534581822
-[355,] 0.5333003050 0.738410240 0.5695481685 0.118196896
-[356,] 0.6283332780 0.021384809 0.3013993963 0.235892471
-[357,] 0.3496081459 0.082318803 0.8034476112 0.615855429
-[358,] 0.6827916105 0.739332259 0.4556267061 0.560452784
-[359,] 0.3037325416 0.954792430 0.5853331985 0.818992345
-[360,] 0.8175444310 0.362225051 0.7151003983 0.228975809
-[361,] 0.0063419391 0.284399928 0.5142549528 0.487628832
-[362,] 0.4775556314 0.584947050 0.5906238395 0.117727362
-[363,] 0.4372084681 0.769685948 0.2747515938 0.682309937
-[364,] 0.7498383273 0.967765797 0.8447801836 0.280101757
-[365,] 0.1267350963 0.504340193 0.0679511335 0.255510229
-[366,] 0.1332432132 0.210321337 0.5455718499 0.371653482
-[367,] 0.4835004443 0.540350976 0.6908350498 0.774367710
-[368,] 0.7049593334 0.203165571 0.7171184889 0.545066704
-[369,] 0.4783587519 0.441262098 0.2402160212 0.846125873
-[370,] 0.3122980180 0.676219228 0.6122906946 0.453429835
-[371,] 0.7974219534 0.361899156 0.3115806549 0.844481082
-[372,] 0.6184745003 0.981996044 0.3197651270 0.157665661
-[373,] 0.6590813969 0.843595678 0.6124570610 0.974553713
-[374,] 0.4819237876 0.249550602 0.3836133203 0.453789817
-[375,] 0.5730831542 0.467314963 0.3064885780 0.033655912
-[376,] 0.7225157402 0.457241144 0.7478901469 0.796643843
-[377,] 0.8063645191 0.499557219 0.0245002492 0.945755220
-[378,] 0.4178847608 0.473695976 0.7174830632 0.230468606
-[379,] 0.3640867800 0.620711620 0.4733614819 0.563877373
[TRUNCATED]
To get the complete diff run:
svnlook diff /svnroot/vinecopula -r 63
Mehr Informationen über die Mailingliste Vinecopula-commits