BiCopGofKendall {CDVine} | R Documentation |
This function performs the goodness-of-fit test based on Kendall's process for bivariate copula data. It computes the Cramer-von Mises and Kolmogorov-Smirnov test statistics, respectively, as well as the according p-values using bootstrapping.
BiCopGofKendall(u1, u2, family, B=100, level=0.05)
u1,u2 |
Data vectors of equal length with values in [0,1]. |
family |
An integer defining the bivariate copula family for which the test is performed: |
B |
Integer; number of bootstrap samples (default: |
level |
Numeric; significance level of the goodness-of-fit test (default: |
This copula goodness-of-fit test is based on Kendall's process as investigated by Genest and Rivest (1993) and Wang and Wells (2000). For rotated copulas the input arguments are transformed and the goodness-of-fit procedure for the corresponding non-rotated copula is used.
p.value.CvM |
P-value of the goodness-of-fit test using the Cramer-von Mises statistic |
p.value.KS |
P-value of the goodness-of-fit test using the Kolmogorov-Smirnov statistic |
statistic.CvM |
The observed Cramer-von Mises test statistic. |
statistic.KS |
The observed Kolmogorov-Smirnov test statistic. |
Jiying Luo, Eike Brechmann
Genest, C. and L.-P. Rivest (1993). Statistical inference procedures for bivariate Archimedean copulas. Journal of the American Statistical Association, 88 (423), 1034-1043.
Luo J. (2011).
Stepwise estimation of D-vines with arbitrary specified copula pairs and EDA Tools.
Diploma thesis, Technische Universitaet Muenchen.
http://mediatum.ub.tum.de/doc/1079291/1079291.pdf.
Wang, W. and M. T. Wells (2000). Model selection and semiparametric inference for bivariate failure-time data. Journal of the American Statistical Association, 95 (449), 62-72.
BiCopIndTest
, BiCopSelect
, BiCopVuongClarke
, BiCopKPlot
, BiCopLambda
# sample from a Gaussian copula par1 = 3 fam1 = 3 dat1 = BiCopSim(500,fam1,par1) ## Not run: # perform the goodness-of-fit test for the true copula gof = BiCopGofKendall(dat1[,1],dat1[,2],fam1) gof$p.value.CvM gof$p.value.KS # perform the goodness-of-fit test for the Frank copula gof = BiCopGofKendall(dat1[,1],dat1[,2],5) gof$p.value.CvM gof$p.value.KS ## End(Not run)