[Vinecopula-commits] r65 - in pkg: man tests/Examples

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Di Apr 22 17:23:47 CEST 2014


Author: etobi
Date: 2014-04-22 17:23:46 +0200 (Tue, 22 Apr 2014)
New Revision: 65

Modified:
   pkg/man/RVineStructureSelect.Rd
   pkg/man/RVineTreePlot.Rd
   pkg/tests/Examples/VineCopula-Ex.Rout.save
Log:
Examples f?\195?\188r RVineStructureSelect und RVineTreePlot angepasst.

Modified: pkg/man/RVineStructureSelect.Rd
===================================================================
--- pkg/man/RVineStructureSelect.Rd	2014-04-22 13:49:04 UTC (rev 64)
+++ pkg/man/RVineStructureSelect.Rd	2014-04-22 15:23:46 UTC (rev 65)
@@ -118,9 +118,7 @@
 data(daxreturns)
 
 # select the R-vine structure, families and parameters
-\dontrun{
-RVM = RVineStructureSelect(daxreturns,c(1:6),progress=TRUE)
-}
+RVM = RVineStructureSelect(daxreturns[,1:4],c(1:6),progress=TRUE)
 
 # specify a C-vine copula model with only Clayton, Gumbel and Frank copulas
 \dontrun{

Modified: pkg/man/RVineTreePlot.Rd
===================================================================
--- pkg/man/RVineTreePlot.Rd	2014-04-22 13:49:04 UTC (rev 64)
+++ pkg/man/RVineTreePlot.Rd	2014-04-22 15:23:46 UTC (rev 65)
@@ -89,6 +89,6 @@
 # re-set random seed for testing
 set.seed(666)
 # plot only the first tree with new coordinates
-RVineTreePlot(data=NULL,RVM=RVM,tree=1,edge.labels=FALSE,P=P)
+P = RVineTreePlot(data=NULL,RVM=RVM,tree=1,edge.labels=FALSE,P=P)
 }
 

Modified: pkg/tests/Examples/VineCopula-Ex.Rout.save
===================================================================
--- pkg/tests/Examples/VineCopula-Ex.Rout.save	2014-04-22 13:49:04 UTC (rev 64)
+++ pkg/tests/Examples/VineCopula-Ex.Rout.save	2014-04-22 15:23:46 UTC (rev 65)
@@ -1,7 +1,7 @@
 
-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)
+Platform: i386-w64-mingw32/i386 (32-bit)
 
 R is free software and comes with ABSOLUTELY NO WARRANTY.
 You are welcome to redistribute it under certain conditions.
@@ -22,3355 +22,3330 @@
 > options(warn = 1)
 > options(pager = "console")
 > library('VineCopula')
-> 
-> base::assign(".oldSearch", base::search(), pos = 'CheckExEnv')
-> cleanEx()
-> nameEx("BB1Copula-class")
-> ### * BB1Copula-class
-> 
-> flush(stderr()); flush(stdout())
-> 
-> ### Name: BB1Copula-class
-> ### Title: Classes '"BB1Copula"', '"surBB1Copula"', '"r90BB1Copula"' and
-> ###   '"r270BB1Copula"'
-> ### Aliases: BB1Copula-class dduCopula,numeric,BB1Copula-method
-> ###   ddvCopula,numeric,BB1Copula-method dduCopula,matrix,BB1Copula-method
-> ###   ddvCopula,matrix,BB1Copula-method getKendallDistr,BB1Copula-method
-> ###   kendallDistribution,BB1Copula-method surBB1Copula-class
-> ###   dduCopula,numeric,surBB1Copula-method
-> ###   ddvCopula,numeric,surBB1Copula-method
-> ###   dduCopula,matrix,surBB1Copula-method
-> ###   ddvCopula,matrix,surBB1Copula-method r90BB1Copula-class
-> ###   dduCopula,numeric,r90BB1Copula-method
-> ###   ddvCopula,numeric,r90BB1Copula-method
-> ###   dduCopula,matrix,r90BB1Copula-method
-> ###   ddvCopula,matrix,r90BB1Copula-method r270BB1Copula-class
-> ###   dduCopula,numeric,r270BB1Copula-method
-> ###   ddvCopula,numeric,r270BB1Copula-method
-> ###   dduCopula,matrix,r270BB1Copula-method
-> ###   ddvCopula,matrix,r270BB1Copula-method
-> ### Keywords: classes
-> 
-> ### ** Examples
-> 
-> showClass("BB1Copula")
-Class "BB1Copula" [package "VineCopula"]
-
-Slots:
-                                                                       
-Name:        family    dimension   parameters  param.names param.lowbnd
-Class:      numeric      integer      numeric    character      numeric
-                                
-Name:   param.upbnd     fullname
-Class:      numeric    character
-
-Extends: 
-Class "copula", directly
-Class "twoParamBiCop", directly
-Class "Copula", by class "copula", distance 2
-> 
-> 
-> 
-> cleanEx()
-> nameEx("BB1Copula")
-> ### * BB1Copula
-> 
-> flush(stderr()); flush(stdout())
-> 
-> ### Name: BB1Copula
-> ### Title: Constructor of the BB1 family and rotated versions thereof
-> ### Aliases: BB1Copula surBB1Copula r90BB1Copula r270BB1Copula
-> ### Keywords: distribution copula
-> 
-> ### ** Examples
-> 
-> library(copula)
-
-Attaching package: 'copula'
-
-The following object is masked from 'package:VineCopula':
-
-    fitCopula
-
-> 
-> persp(BB1Copula(c(1,1.5)),dCopula, zlim=c(0,10))
-Warning in persp.default(xis, yis, zmat, theta = theta, phi = phi, expand = expand,  :
-  surface extends beyond the box
-> persp(surBB1Copula(c(1,1.5)),dCopula, zlim=c(0,10))
-Warning in persp.default(xis, yis, zmat, theta = theta, phi = phi, expand = expand,  :
-  surface extends beyond the box
-> persp(r90BB1Copula(c(-1,-1.5)),dCopula, zlim=c(0,10))
-Warning in persp.default(xis, yis, zmat, theta = theta, phi = phi, expand = expand,  :
-  surface extends beyond the box
-> persp(r270BB1Copula(c(-1,-1.5)),dCopula, zlim=c(0,10))
-Warning in persp.default(xis, yis, zmat, theta = theta, phi = phi, expand = expand,  :
-  surface extends beyond the box
-> 
-> 
-> 
-> cleanEx()
-
-detaching 'package:copula'
-
-> nameEx("BB6Copula-class")
-> ### * BB6Copula-class
-> 
-> flush(stderr()); flush(stdout())
-> 
-> ### Name: BB6Copula-class
-> ### Title: Classes '"BB6Copula"', '"surBB6Copula"', '"r90BB6Copula"' and
-> ###   '"r270BB6Copula"'
-> ### Aliases: BB6Copula-class dduCopula,numeric,BB6Copula-method
-> ###   ddvCopula,numeric,BB6Copula-method dduCopula,matrix,BB6Copula-method
-> ###   ddvCopula,matrix,BB6Copula-method getKendallDistr,BB6Copula-method
-> ###   kendallDistribution,BB6Copula-method surBB6Copula-class
-> ###   dduCopula,numeric,surBB6Copula-method
-> ###   ddvCopula,numeric,surBB6Copula-method
-> ###   dduCopula,matrix,surBB6Copula-method
-> ###   ddvCopula,matrix,surBB6Copula-method r90BB6Copula-class
-> ###   dduCopula,numeric,r90BB6Copula-method
-> ###   ddvCopula,numeric,r90BB6Copula-method
-> ###   dduCopula,matrix,r90BB6Copula-method
-> ###   ddvCopula,matrix,r90BB6Copula-method r270BB6Copula-class
-> ###   dduCopula,numeric,r270BB6Copula-method
-> ###   ddvCopula,numeric,r270BB6Copula-method
-> ###   dduCopula,matrix,r270BB6Copula-method
-> ###   ddvCopula,matrix,r270BB6Copula-method
-> ### Keywords: classes
-> 
-> ### ** Examples
-> 
-> showClass("BB6Copula")
-Class "BB6Copula" [package "VineCopula"]
-
-Slots:
-                                                                       
-Name:        family    dimension   parameters  param.names param.lowbnd
-Class:      numeric      integer      numeric    character      numeric
-                                
-Name:   param.upbnd     fullname
-Class:      numeric    character
-
-Extends: 
-Class "copula", directly
-Class "twoParamBiCop", directly
-Class "Copula", by class "copula", distance 2
-> 
-> 
-> 
-> cleanEx()
-> nameEx("BB6Copula")
-> ### * BB6Copula
-> 
-> flush(stderr()); flush(stdout())
-> 
-> ### Name: BB6Copula
-> ### Title: Constructor of the BB6 family and its derivatives
-> ### Aliases: BB6Copula surBB6Copula r90BB6Copula r270BB6Copula
-> 
-> ### ** Examples
-> 
-> library(copula)
-
-Attaching package: 'copula'
-
-The following object is masked from 'package:VineCopula':
-
-    fitCopula
-
-> 
-> persp(BB6Copula(c(1,1.5)),dCopula, zlim=c(0,10))
-Warning in persp.default(xis, yis, zmat, theta = theta, phi = phi, expand = expand,  :
-  surface extends beyond the box
-> persp(surBB6Copula(c(1,1.5)),dCopula, zlim=c(0,10))
-Warning in persp.default(xis, yis, zmat, theta = theta, phi = phi, expand = expand,  :
-  surface extends beyond the box
-> persp(r90BB6Copula(c(-1,-1.5)),dCopula, zlim=c(0,10))
-Warning in persp.default(xis, yis, zmat, theta = theta, phi = phi, expand = expand,  :
-  surface extends beyond the box
-> persp(r270BB6Copula(c(-1,-1.5)),dCopula, zlim=c(0,10))
-Warning in persp.default(xis, yis, zmat, theta = theta, phi = phi, expand = expand,  :
-  surface extends beyond the box
-> 
-> 
-> 
-> cleanEx()
-
-detaching 'package:copula'
-
-> nameEx("BB7Copula-class")
-> ### * BB7Copula-class
-> 
-> flush(stderr()); flush(stdout())
-> 
-> ### Name: BB7Copula-class
-> ### Title: Classes '"BB7Copula"', '"surBB7Copula"', '"r90BB7Copula"' and
-> ###   '"r270BB7Copula"'
-> ### Aliases: BB7Copula-class dduCopula,numeric,BB7Copula-method
-> ###   ddvCopula,numeric,BB7Copula-method dduCopula,matrix,BB7Copula-method
-> ###   ddvCopula,matrix,BB7Copula-method getKendallDistr,BB7Copula-method
-> ###   kendallDistribution,BB7Copula-method surBB7Copula-class
-> ###   dduCopula,numeric,surBB7Copula-method
-> ###   ddvCopula,numeric,surBB7Copula-method
-> ###   dduCopula,matrix,surBB7Copula-method
-> ###   ddvCopula,matrix,surBB7Copula-method r90BB7Copula-class
-> ###   dduCopula,numeric,r90BB7Copula-method
-> ###   ddvCopula,numeric,r90BB7Copula-method
-> ###   dduCopula,matrix,r90BB7Copula-method
-> ###   ddvCopula,matrix,r90BB7Copula-method r270BB7Copula-class
-> ###   dduCopula,numeric,r270BB7Copula-method
-> ###   ddvCopula,numeric,r270BB7Copula-method
-> ###   dduCopula,matrix,r270BB7Copula-method
-> ###   ddvCopula,matrix,r270BB7Copula-method
-> ### Keywords: classes
-> 
-> ### ** Examples
-> 
-> showClass("BB7Copula")
-Class "BB7Copula" [package "VineCopula"]
-
-Slots:
-                                                                       
-Name:        family    dimension   parameters  param.names param.lowbnd
-Class:      numeric      integer      numeric    character      numeric
-                                
-Name:   param.upbnd     fullname
-Class:      numeric    character
-
-Extends: 
-Class "copula", directly
-Class "twoParamBiCop", directly
-Class "Copula", by class "copula", distance 2
-> 
-> 
-> 
-> cleanEx()
-> nameEx("BB7Copula")
-> ### * BB7Copula
-> 
-> flush(stderr()); flush(stdout())
-> 
-> ### Name: BB7Copula
-> ### Title: Constructor of the BB7 family and its derivatives
-> ### Aliases: BB7Copula surBB7Copula r90BB7Copula r270BB7Copula
-> 
-> ### ** Examples
-> 
-> library(copula)
-
-Attaching package: 'copula'
-
-The following object is masked from 'package:VineCopula':
-
-    fitCopula
-
-> 
-> persp(BB7Copula(c(1,1.5)),dCopula, zlim=c(0,10))
-Warning in persp.default(xis, yis, zmat, theta = theta, phi = phi, expand = expand,  :
-  surface extends beyond the box
-> persp(surBB7Copula(c(1,1.5)),dCopula, zlim=c(0,10))
-Warning in persp.default(xis, yis, zmat, theta = theta, phi = phi, expand = expand,  :
-  surface extends beyond the box
-> persp(r90BB7Copula(c(-1,-1.5)),dCopula, zlim=c(0,10))
-Warning in persp.default(xis, yis, zmat, theta = theta, phi = phi, expand = expand,  :
-  surface extends beyond the box
-> persp(r270BB7Copula(c(-1,-1.5)),dCopula, zlim=c(0,10))
-Warning in persp.default(xis, yis, zmat, theta = theta, phi = phi, expand = expand,  :
-  surface extends beyond the box
-> 
-> 
-> 
-> cleanEx()
-
-detaching 'package:copula'
-
-> nameEx("BB8Copula-class")
-> ### * BB8Copula-class
-> 
-> flush(stderr()); flush(stdout())
-> 
-> ### Name: BB8Copula-class
-> ### Title: Classes '"BB8Copula"', '"surBB8Copula"', '"r90BB8Copula"' and
-> ###   '"r270BB8Copula"'
-> ### Aliases: BB8Copula-class dduCopula,numeric,BB8Copula-method
-> ###   ddvCopula,numeric,BB8Copula-method dduCopula,matrix,BB8Copula-method
-> ###   ddvCopula,matrix,BB8Copula-method getKendallDistr,BB8Copula-method
-> ###   kendallDistribution,BB8Copula-method surBB8Copula-class
-> ###   dduCopula,numeric,surBB8Copula-method
-> ###   ddvCopula,numeric,surBB8Copula-method
-> ###   dduCopula,matrix,surBB8Copula-method
-> ###   ddvCopula,matrix,surBB8Copula-method r90BB8Copula-class
-> ###   dduCopula,numeric,r90BB8Copula-method
-> ###   ddvCopula,numeric,r90BB8Copula-method
-> ###   dduCopula,matrix,r90BB8Copula-method
-> ###   ddvCopula,matrix,r90BB8Copula-method r270BB8Copula-class
-> ###   dduCopula,numeric,r270BB8Copula-method
-> ###   ddvCopula,numeric,r270BB8Copula-method
-> ###   dduCopula,matrix,r270BB8Copula-method
-> ###   ddvCopula,matrix,r270BB8Copula-method fitCopula,twoParamBiCop-method
-> ### Keywords: classes
-> 
-> ### ** Examples
-> 
-> showClass("BB8Copula")
-Class "BB8Copula" [package "VineCopula"]
-
-Slots:
-                                                                       
-Name:        family    dimension   parameters  param.names param.lowbnd
-Class:      numeric      integer      numeric    character      numeric
-                                
-Name:   param.upbnd     fullname
-Class:      numeric    character
-
-Extends: 
-Class "copula", directly
-Class "twoParamBiCop", directly
-Class "Copula", by class "copula", distance 2
-> 
-> 
-> 
-> cleanEx()
-> nameEx("BB8Copula")
-> ### * BB8Copula
-> 
-> flush(stderr()); flush(stdout())
-> 
-> ### Name: BB8Copula
-> ### Title: Constructor of the BB8 family and its derivatives
-> ### Aliases: BB8Copula surBB8Copula r90BB8Copula r270BB8Copula
-> 
-> ### ** Examples
-> 
-> library(copula)
-
-Attaching package: 'copula'
-
-The following object is masked from 'package:VineCopula':
-
-    fitCopula
-
-> 
-> persp(BB8Copula(c(1,0.5)),dCopula, zlim=c(0,10))
-> persp(surBB8Copula(c(1,0.5)),dCopula, zlim=c(0,10))
-> persp(r90BB8Copula(c(-1,-0.5)),dCopula, zlim=c(0,10))
-> persp(r270BB8Copula(c(-1,-0.5)),dCopula, zlim=c(0,10))
-> 
-> 
-> 
-> cleanEx()
-
-detaching 'package:copula'
-
-> nameEx("BetaMatrix")
-> ### * BetaMatrix
-> 
-> flush(stderr()); flush(stdout())
-> 
-> ### Name: BetaMatrix
-> ### Title: Matrix of empirical Blomqvist's beta values
-> ### Aliases: BetaMatrix
-> 
-> ### ** Examples
-> 
-> data(daxreturns)
-> Data = as.matrix(daxreturns)
-> 
-> # compute the empirical Blomqvist's betas
-> beta = BetaMatrix(Data)
-> 
-> 
-> 
-> cleanEx()
-> nameEx("BiCopCDF")
-> ### * BiCopCDF
-> 
-> flush(stderr()); flush(stdout())
-> 
-> ### Name: BiCopCDF
-> ### Title: Distribution function of a bivariate copula
-> ### Aliases: BiCopCDF
-> 
-> ### ** Examples
-> 
-> # simulate from a bivariate Clayton
-> simdata = BiCopSim(300,3,3.4)
-> 
-> # evaluate the distribution function of the bivariate t-copula
-> u1 = simdata[,1]
-> u2 = simdata[,2]
-> BiCopCDF(u1,u2,3,3.4)
-  [1] 0.212083894 0.560454175 0.196829776 0.859783373 0.334142797 0.138883599
-  [7] 0.552748610 0.656946696 0.716294284 0.358902123 0.657106132 0.406649144
- [13] 0.215249319 0.010762322 0.680744432 0.429168263 0.336836485 0.754999947
- [19] 0.478876720 0.591381592 0.743614123 0.684320242 0.501994536 0.019720627
- [25] 0.673692866 0.461672664 0.318172610 0.041830170 0.272430716 0.539624409
- [31] 0.690952756 0.357404390 0.478385703 0.450454976 0.081735412 0.325850276
- [37] 0.270163818 0.464160879 0.697817469 0.770254930 0.402432651 0.309902564
- [43] 0.526755239 0.440604149 0.157859951 0.125915290 0.623294168 0.739830600
- [49] 0.371783278 0.723334913 0.516814728 0.269809505 0.445858863 0.109397786
- [55] 0.822399359 0.909295094 0.294693765 0.055312093 0.427042357 0.403252652
- [61] 0.845573559 0.325266686 0.630782109 0.357571974 0.203263111 0.321058009
- [67] 0.032144353 0.826230667 0.484706552 0.844421805 0.608301620 0.175590037
- [73] 0.609058333 0.163878464 0.101571465 0.538136460 0.274644551 0.339289595
- [79] 0.294216757 0.195381304 0.277706814 0.421733480 0.720333595 0.049782599
- [85] 0.565454106 0.606022665 0.691741950 0.371062856 0.601897391 0.591440556
- [91] 0.201688601 0.758395667 0.600742911 0.704561061 0.823026172 0.574257107
- [97] 0.099157544 0.251281107 0.106087540 0.300755602 0.189355553 0.383442247
-[103] 0.156051138 0.353445260 0.237769014 0.569868697 0.754009708 0.626534957
-[109] 0.642565610 0.746343146 0.174386590 0.276468326 0.793197597 0.128246949
-[115] 0.403133907 0.218942785 0.337329582 0.358487519 0.603040975 0.358813218
-[121] 0.270584669 0.584756888 0.291400991 0.270925282 0.453995540 0.750041775
-[127] 0.419655276 0.292947806 0.211477158 0.367187001 0.403616732 0.263279705
-[133] 0.466439291 0.060463864 0.414509798 0.037596575 0.254942295 0.205299452
-[139] 0.174436459 0.449884240 0.024025747 0.703587274 0.030608188 0.210400866
-[145] 0.093855295 0.142735752 0.761364232 0.464621321 0.061121298 0.049605515
-[151] 0.394449212 0.413216316 0.374454880 0.168265886 0.055593257 0.097151257
-[157] 0.780802798 0.227744822 0.065636001 0.870926086 0.510225526 0.405327388
-[163] 0.845888486 0.768194100 0.251842178 0.746537224 0.380903910 0.061307470
-[169] 0.290451789 0.578210814 0.667105491 0.436226140 0.501831663 0.314446545
-[175] 0.343212498 0.260100773 0.643573510 0.736279214 0.480576518 0.747377388
-[181] 0.084991510 0.625430254 0.563728676 0.065672797 0.586906305 0.383323904
-[187] 0.665138618 0.182143650 0.322690699 0.150906032 0.377309335 0.652937289
-[193] 0.167981587 0.764145834 0.112547545 0.094783549 0.792890037 0.121846529
-[199] 0.506278225 0.227685925 0.449045336 0.931289729 0.876824814 0.350126804
-[205] 0.010994635 0.786543245 0.709228011 0.596225473 0.378512582 0.664875538
-[211] 0.373815801 0.426252115 0.280636713 0.083968169 0.814257670 0.515317294
-[217] 0.328967379 0.099903254 0.377995332 0.473178827 0.031442176 0.447588371
-[223] 0.217327056 0.361663573 0.067611532 0.801212727 0.247607998 0.049270220
-[229] 0.576458572 0.324353916 0.136902467 0.001605048 0.257187329 0.474040408
-[235] 0.437713533 0.456113202 0.577646467 0.085121494 0.715134572 0.457893436
-[241] 0.498003300 0.838971972 0.503169431 0.045336633 0.555881808 0.022418980
-[247] 0.194331580 0.334462487 0.373599846 0.438035879 0.509068595 0.599445606
-[253] 0.468924572 0.387566042 0.655708457 0.735283578 0.007562104 0.489784093
-[259] 0.562107349 0.302752252 0.766853423 0.218580395 0.381560134 0.755457200
-[265] 0.955922687 0.272025101 0.251443038 0.057390884 0.289182961 0.155876041
-[271] 0.393765386 0.507388247 0.120671623 0.799010545 0.523637750 0.767031675
-[277] 0.010792082 0.619446682 0.047529687 0.786968380 0.413820169 0.318351521
-[283] 0.835610923 0.218595381 0.278001748 0.129935495 0.147382642 0.715055153
-[289] 0.544744934 0.786205589 0.344101052 0.302395620 0.488473797 0.066509090
-[295] 0.889908357 0.401278597 0.705956499 0.752430964 0.408975709 0.316904963
-> 
-> 
-> 
-> cleanEx()
-> nameEx("BiCopChiPlot")
-> ### * BiCopChiPlot
-> 
-> flush(stderr()); flush(stdout())
-> 
-> ### Name: BiCopChiPlot
-> ### Title: Chi-plot for bivariate copula data
-> ### Aliases: BiCopChiPlot
-> 
-> ### ** Examples
-> 
-> ## Not run: 
-> ##D # chi-plots for bivariate Gaussian copula data
-> ##D n = 500
-> ##D tau = 0.5
-> ##D 
-> ##D # simulate copula data
-> ##D fam = 1	
-> ##D theta = BiCopTau2Par(fam,tau)
-> ##D dat = BiCopSim(n,fam,theta)	
-> ##D 
-> ##D # create chi-plots
-> ##D dev.new(width=16,height=5)
-> ##D par(mfrow=c(1,3))
-> ##D BiCopChiPlot(dat[,1],dat[,2],xlim=c(-1,1),ylim=c(-1,1),
-> ##D              main="General chi-plot")
-> ##D BiCopChiPlot(dat[,1],dat[,2],mode="lower",xlim=c(-1,1),
-> ##D              ylim=c(-1,1),main="Lower chi-plot")
-> ##D BiCopChiPlot(dat[,1],dat[,2],mode="upper",xlim=c(-1,1),
-> ##D              ylim=c(-1,1),main="Upper chi-plot")
-> ## End(Not run)
-> 
-> 
-> 
-> cleanEx()
-> nameEx("BiCopDeriv")
-> ### * BiCopDeriv
-> 
-> flush(stderr()); flush(stdout())
-> 
-> ### Name: BiCopDeriv
-> ### Title: Derivatives of a bivariate copula density
-> ### Aliases: BiCopDeriv
-> 
-> ### ** Examples
-> 
-> # simulate from a bivariate t-copula
-> simdata = BiCopSim(300,2,-0.7,par2=4)
-> 
-> # derivative of the bivariate t-copula with respect to the first parameter
-> u1 = simdata[,1]
-> u2 = simdata[,2]
-> BiCopDeriv(u1,u2,2,-0.7,par2=4, deriv="par")
-  [1]  -1.118981963   1.240853696  -1.001064211   0.126342186   1.175103086
-  [6]   1.125284074  -2.660900650  -2.472195467   1.023015475  -1.226835099
- [11] -10.758312703  -0.060805698  -1.275771122  -0.874257992  -5.229438212
- [16]  -1.996785307  -0.024314703  -0.340297829  -1.124279340  -2.830928257
- [21]  -0.644128690  -1.902583339  -0.198026426  -5.534636646  -0.399781564
- [26]   0.435400718  -0.424885018   1.472901008  -2.384264853  -2.524411180
- [31]  -7.785438426  -1.363561693  -1.835639592  -0.722528253  -6.472291697
- [36]  -0.716665042  -0.964105867   0.829886233  -4.540361690   1.351436336
- [41]  -1.503828622  -1.074008721  -2.420782826  -0.457655215   1.239990732
- [46]   1.451559193   1.125103668   0.869236569  -1.879796413  -1.231228404
- [51]  -2.424107089   1.829094173  -1.221019510  -2.559081446  -1.233727812
- [56]   1.872628051  -1.838289517   0.971594798  -0.096706898  -1.937842204
- [61] -15.237257119   0.172804942  -2.778179365  -0.368238987  -3.191034202
- [66]   1.081925107 -13.105195405  -1.253692526  -2.123195334  -8.688276102
- [71]  -1.503515318   0.256531438  -2.674138975  -4.198369584  -5.259632795
- [76]  -1.944954160  -1.969911957   0.006893071   1.207272916   0.571959168
- [81]  -0.132434126  -0.754275953  -4.565334109   0.127084068  -2.903169549
- [86]   0.771316852  -4.357864429   0.489405734  -0.218840978   1.257765042
- [91]   0.720810321  -3.023537238  -5.465362366   0.055533560  -2.703654480
- [96]  -2.809374993  -2.368171453  -2.796443300  -5.602431270  -1.693541846
-[101]   0.551536277  -1.064635971  -2.851261121   0.383686061  -2.937039105
-[106] -13.728663798   1.428865348  -4.156683579   1.475522589 -11.428897046
-[111]   1.042581628  -2.329817184  -3.371593709   1.422863380   0.041637025
-[116]   1.087794501  -2.304816570  -1.944080252  -1.899435223  -2.039960766
-[121]  -2.645050409  -6.650555229   0.050104775   0.851039002   1.383789144
-[126]   1.465850488  -2.014890698   0.938868515  -2.392303876   1.122254766
-[131]  -1.525108901  -2.071212850  -1.173020644 -10.741866594  -0.542828355
-[136]   1.515200988   0.630401901   0.694797858   0.931185696  -0.680191222
-[141]  -7.933722404  -5.163276704   1.664827305   0.960737875   1.063045879
-[146]   1.342918851 -25.249465414  -1.393407553   1.532198588  -6.911077681
-[151]   0.376116964  -2.132593253   1.552339321  -3.505820153  -1.224401790
-[156]   1.227776973   0.353972461  -2.323316239  -0.313598837  -0.566267188
-[161]  -2.330830899   1.274204534   1.293889346   0.860444774  -2.469578460
-[166] -37.208160647  -0.658022946  -0.468399340   0.542603267   1.471761927
-[171] -62.570186831  -2.007473905  -2.147550775   0.259715654  -1.822814641
-[176]   1.381625780  -3.213788742 -28.991603753  -1.229075644  -3.627148879
-[181]  -0.101623278  -4.587179691   0.581309497  -9.140049046  -2.507966161
-[186]  -2.212019166  -9.855455970  -1.589138378  -0.337898112  -2.553649116
-[191]  -2.226506883   1.333901700   0.465082093   1.189110937   0.796068401
-[196]   1.443132908  -3.501076181  -0.501800492  -2.291129850   0.935368493
-[201]  -1.064749466   1.467016724   1.082767823  -1.259347011 -35.328425259
-[206] -54.951284051   0.718174055  -2.464860924  -1.312713214   0.813159659
-[211]  -2.210898561  -0.448716041  -1.620526551  -2.795506995   1.473304529
-[216]  -5.057278714  -2.325488643  -6.612891371   1.047891665   1.184335554
-[221]   1.067936715  -1.893917726  -1.660850454   1.235448817   1.395848509
-[226]  -8.352631627   0.661067847 -10.045949778   1.301830099   1.184362514
-[231]  -2.365111887 -19.375622882   0.787353636  -1.284525224  -1.465763628
-[236]   1.487875678  -2.800629638   0.974747012  -3.893986259  -1.347791384
-[241]  -1.715161311   1.344923130  -2.191660590   0.729214728  -4.251170941
-[246] -15.846996489   0.963319101  -2.045913223  -2.214253517   0.123732841
-[251]  -1.130187683  -0.976720057   1.550396563  -0.114614937  -2.106725798
-[256]  -3.543205014 -64.153096610  -1.674467836  -2.013424285  -2.506361843
-[261]   0.171864835   1.109748552   1.058702426   0.607026838   0.841762192
-[266]   1.600486017  -0.341279447   1.218882366  -1.075804146  -3.976274166
-[271]   1.462331510  -2.327053523   1.443964144 -70.883566817  -0.662165420
-[276]  -1.690102935 -50.916636504  -3.285496238   1.214680711   1.243536650
-[281]  -0.209042356  -1.987493543   0.412999360  -3.236351739   1.359980628
-[286]  -1.527350949   1.444523027  -2.321816594  -2.549388281   0.552707478
-[291]   1.307238920   1.553288676  -2.277551572  -4.393119872   1.180012547
-[296]  -1.006935254  -0.716277972  -0.594563456  -2.172846043  -1.984262894
-> 
-> 
-> 
-> cleanEx()
-> nameEx("BiCopDeriv2")
-> ### * BiCopDeriv2
-> 
-> flush(stderr()); flush(stdout())
-> 
-> ### Name: BiCopDeriv2
-> ### Title: Second derivatives of a bivariate copula density
-> ### Aliases: BiCopDeriv2
-> 
-> ### ** Examples
-> 
-> # simulate from a bivariate t-copula
-> simdata = BiCopSim(300,2,-0.7,par2=4)
-> 
-> # second derivative of the bivariate t-copula with respect to the first parameter
-> u1 = simdata[,1]
-> u2 = simdata[,2]
-> BiCopDeriv2(u1,u2,2,-0.7,par2=4, deriv="par")
-  [1]    2.4126542   -6.6825108   -6.3560370  -13.7227857   -9.1816929
-  [6]   -7.0908205   13.7290309   10.7473379    1.2577657    2.6630769
- [11]   45.1413216   -5.6405356    3.4557714  -38.1175487   23.8842516
- [16]   10.4429381   -3.4900896   -4.0350153   -5.2822373   14.4093322
- [21]   -2.3705610    6.3865847   -2.3729617   -8.3403632   -1.7953292
- [26]   -5.9126744   -0.8925703   -2.7198451   12.1687196   13.2898122
- [31]   34.8767633    5.5283219    6.8140897    0.5179240   12.8722339
- [36]   -1.9694262    2.3857559   -7.1967954   19.9757800   -0.8634186
- [41]    5.8194993    3.3938077    7.1423000   -5.1528390   -6.5129152
- [46]   -2.6078043   -6.5350832   -6.9423348    9.5969194    1.2028442
- [51]   12.2097919   -5.3415160    2.3088684    6.2549771   -6.3055972
- [56]  -20.6839367    8.6985442    1.8900924   -7.2938766    9.6259884
- [61]  -15.8136161   -4.4191251   13.3567417   -1.6699869   15.6181921
- [66]   -8.2228638   49.6433734   -6.8637577   11.5149595  -10.1757433
- [71]    5.7891358   -5.1789980   13.2930910   17.9367741   11.1038423
- [76]    9.7799834    9.3298570   -3.7109533   -7.6361988   -5.8621277
- [81]   -7.0977482    0.3699164   18.6443999  -12.3991863   14.2560643
- [86]   -6.1678671   19.3905631   -7.4826160   -2.0968065   -6.4709585
- [91]   -6.1599241    7.7973748   19.3468978   -4.3365165   -3.1372378
- [96]   14.3722621  -12.2920083   14.3064742   16.3602446    4.6174577
-[101]   -5.8752261    2.9774240   11.4235543   -6.1721458   13.0711948
-[106]   24.5566247   -2.0566903   19.3946357   -3.4040873   46.5514372
-[111]   -6.6975421   11.8752549    4.8264870   -1.9410271   -4.8470163
-[116]   -6.5319545   11.8388787    8.7842751    8.5351932   10.8108849
-[121]   13.7383533   17.5443858   -3.4835638   -6.5227577   -7.3817498
-[126]   -3.1497797   10.5288361   -7.0505394   10.7116425   -9.1255948
-[131]    6.4561544    6.1147706   -0.1415321   47.2160109   -2.1404643
-[136]   -3.2675803   -5.8061782   -6.0783318   -6.6882969    0.2205718
-[141]    9.2056534   22.6513172   -5.4130890   -6.4797445   -8.6119575
-[146]   -6.1626208   99.0525948    5.6320135   -4.5034060  -10.8423355
-[151]   -8.2161180   11.7010068   -3.1354411   10.6979666   -7.4363695
-[156]   -7.9862145   -7.0399481   10.7286487   -9.0056350  -19.8533850
-[161]   10.9014112   -0.7675042   -0.2967231   -7.3862615    9.1439497
-[166]  155.9358951   -1.0080337   -9.1237377   -5.7171014   -2.9464925
-[171]  269.9285276   10.3593989    8.7543815   -4.7214883    7.2427847
-[176]   -6.7186224   15.3700517  124.6436795   -9.6978141   11.7143732
-[181]   -7.6979536   20.5984504   -5.7257439   40.5312907   12.7734411
-[186]   12.0655708   42.4723521    4.4524000   -4.4733160    9.1906767
-[191]   12.1270553   -0.8568985   -5.9649734   -7.0021920  -23.9452815
-[196]   -6.2800218    5.3513165   -3.9053336   10.6781184   -6.4459971
-[201]    0.4934674   -2.4424125  -13.7947217    2.6918629  -15.0437654
-[206]  179.5492436   -6.4095059   12.3367635    5.0010992   -6.3084576
-[211]   12.1575256   -3.7222823    6.9552673  -14.7678286   -5.2660209
-[216]  -11.0043502   12.5483203   25.2705550  -12.1320323   -7.5170928
-[221]  -16.7607915    9.6529562    5.9831467   -9.2588542   -1.5943981
-[226]   19.2252029   -5.8827620   41.3950758   -0.7504865   -8.7125535
-[231]    7.1471377 -182.3423219  -11.5964015    0.1386318    5.9833540
-[236]   -6.7067508   14.3516973   -9.2066813   15.6816459    5.2243435
-[241]    1.1197675   -0.8486390   11.8796392    2.1755199    7.3798075
-[246]  -19.7251148   -6.5430234   10.6690874   12.1767844  -16.2087793
-[251]    3.8184437    2.4339272   -5.1251428   -4.2674313    8.5722830
-[256]   12.3852346  276.5338339    3.0855253    9.9835689   12.7594328
-[261]   -6.1429545   -6.5277846   -8.7959204   -6.8613633    3.2834040
-[266]   -6.8909722   -1.5026474    0.2997642    3.2883771   18.6179306
-[271]   -8.1021536   11.2468036   -5.3373429  195.6539596    0.6054940
-[276]    0.9947356  122.5599083   16.1741216    0.2079989   -7.1625500
-[281]   -4.9097796    7.9203020  -10.0926920   15.9586637  -11.5061335
-[286]    1.7095188   -4.9261936    7.3923584   13.3974394   -7.5603040
-[291]   -9.6068616   -8.6709300   12.2354089   11.2373337  -17.6110050
-[296]    2.1594059   -0.8513871   -2.9233828   12.0301834   10.0336656
-> 
-> 
-> 
-> cleanEx()
-> nameEx("BiCopEst")
-> ### * BiCopEst
-> 
-> flush(stderr()); flush(stdout())
-> 
-> ### Name: BiCopEst
-> ### Title: Parameter estimation for bivariate copula data using inversion
-> ###   of Kendall's tau or maximum likelihood estimation
-> ### Aliases: BiCopEst
-> 
-> ### ** Examples
-> 
-> ## Example 1: bivariate Gaussian copula
-> dat = BiCopSim(500,1,0.7)
-> u1 = dat[,1]
-> v1 = dat[,2]
-> 
-> # empirical Kendall's tau
-> tau1 = cor(u1,v1,method="kendall")
-> 
-> # inversion of empirical Kendall's tau 
-> BiCopTau2Par(1,tau1)
-[1] 0.7045111
-> BiCopEst(u1,v1,family=1,method="itau")$par
-[1] 0.7045111
-> 
-> # maximum likelihood estimate for comparison
-> BiCopEst(u1,v1,family=1,method="mle")$par
-[1] 0.703239
-> 
-> 
-> ## Example 2: bivariate Clayton and survival Gumbel copulas
-> # simulate from a Clayton copula
-> dat = BiCopSim(500,3,2.5)
-> u2 = dat[,1]
-> v2 = dat[,2]
-> 
-> # empirical Kendall's tau
-> tau2 = cor(u2,v2,method="kendall")
-> 
-> # inversion of empirical Kendall's tau for the Clayton copula
-> BiCopTau2Par(3,tau2)
-[1] 2.480802
-> BiCopEst(u2,v2,family=3,method="itau",se=TRUE) 
-$par
-[1] 2.480802
-
-$par2
-[1] 0
-
-$se
-[1] 0.2366735
-
-$se2
-[1] 0
-
-> 
-> # inversion of empirical Kendall's tau for the survival Gumbel copula
-> BiCopTau2Par(14,tau2)
-[1] 2.240401
-> BiCopEst(u2,v2,family=14,method="itau",se=TRUE)
-$par
-[1] 2.240401
-
-$par2
-[1] 0
-
-$se
-[1] 0.1183367
-
-$se2
-[1] 0
-
-> 
-> # maximum likelihood estimates for comparison
-> BiCopEst(u2,v2,family=3,method="mle",se=TRUE)
-$par
-[1] 2.370793
-
-$par2
-[1] 0
-
-$se
-[1] 0.1337379
-
-$se2
-[1] 0
-
-> BiCopEst(u2,v2,family=14,method="mle",se=TRUE)
-$par
-[1] 2.244569
-
-$par2
-[1] 0
-
-$se
-[1] 0.08094233
-
-$se2
-[1] 0
-
->  
-> 
-> 
-> 
-> cleanEx()
-> nameEx("BiCopGofTest")
-> ### * BiCopGofTest
-> 
-> flush(stderr()); flush(stdout())
-> 
-> ### Name: BiCopGofTest
-> ### Title: Goodness-of-fit test for bivariate copulas
-> ### Aliases: BiCopGofTest
-> 
-> ### ** Examples
-> 
-> # simulate from a bivariate Clayton copula
-> 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)
-$p.value
-         [,1]
-[1,] 0.174567
-
-$statistic
-        [,1]
-[1,] 1.84328
-
-> 
-> # perform Kendall's goodness-of-fit test for the Frank copula
-> BiCopGofTest(u1,u2,family=5)
-$p.value
-         [,1]
-[1,] 0.499615
-
-$statistic
-          [,1]
-[1,] 0.4557542
-
-> 
-> ## Not run: 
-> ##D # perform Kendall's goodness-of-fit test for the true copula
-> ##D gof = BiCopGofTest(u1,u2,family=3,method="kendall")
-> ##D gof$p.value.CvM
-> ##D gof$p.value.KS
-> ##D 
-> ##D # perform Kendall's goodness-of-fit test for the Frank copula
-> ##D gof = BiCopGofTest(u1,u2,family=5,method="kendall")
-> ##D gof$p.value.CvM
-> ##D gof$p.value.KS
-> ## End(Not run)
-> 
-> 
-> 
-> cleanEx()
-> nameEx("BiCopHfunc")
-> ### * BiCopHfunc
-> 
-> flush(stderr()); flush(stdout())
-> 
-> ### Name: BiCopHfunc
-> ### Title: Conditional distribution function (h-function) of a bivariate
-> ###   copula
-> ### Aliases: BiCopHfunc
-> 
-> ### ** Examples
-> 
-> # load data set
-> data(daxreturns)
-> 
-> # h-functions of the Gaussian copula
-> h1 = BiCopHfunc(daxreturns[,2],daxreturns[,1],1,0.5)
-> 
-> 
-> 
-> cleanEx()
-> nameEx("BiCopHfuncDeriv")
-> ### * BiCopHfuncDeriv
-> 
-> flush(stderr()); flush(stdout())
-> 
-> ### Name: BiCopHfuncDeriv
-> ### Title: Derivatives of the h-function of a bivariate copula
-> ### Aliases: BiCopHfuncDeriv
-> 
-> ### ** Examples
-> 
-> # simulate from a bivariate t-copula
-> simdata = BiCopSim(300,2,-0.7,par2=4)
-> 
-> # derivative of the conditional bivariate t-copula 
-> # with respect to the first parameter
-> u1 = simdata[,1]
-> u2 = simdata[,2]
-> BiCopHfuncDeriv(u1,u2,2,-0.7,par2=4, deriv="par")
-  [1]  0.188249864 -0.529552481 -0.873071979 -0.088028377  0.764465081
-  [6]  0.268742673  0.225414839  0.003745044 -0.250411287 -0.552223280
- [11]  0.542208002  0.733893277  0.171342121  0.040807295  0.271432180
- [16] -0.194478681  0.539020302 -0.179847959  0.857056553  0.165863800
- [21] -0.167799319 -0.078433467 -0.493630542  0.014446390 -0.259425789
- [26] -0.611885828  0.430828031  0.081037733 -0.034159823  0.180985090
- [31]  0.348575968  0.309101636  0.490238920 -0.491592260 -0.833857762
- [36] -0.683462885  0.269070347 -0.635325777  0.174910232 -0.232964155
- [41] -0.415391436  0.301526190  0.625251401  0.781396939  0.315011241
- [46]  0.272627317 -0.447754453 -0.281985372  0.171307540 -0.133608127
- [51]  0.291907921 -0.739724153  0.574547234  0.027070515 -0.078697407
- [56] -0.055992298  0.122430683  0.125977620  0.815021190 -0.275509931
- [61]  0.002381546  0.545961005  0.080450266  0.523905668 -0.172254706
- [66]  0.701785048 -0.172723789 -0.075921055 -0.050254540 -0.004517698
- [71] -0.168177303  0.276160659  0.085267141 -0.493157648 -0.803393801
[TRUNCATED]

To get the complete diff run:
    svnlook diff /svnroot/vinecopula -r 65


Mehr Informationen über die Mailingliste Vinecopula-commits