Multivariate dependence with copulas

November 17, 2008

(This article was first published on Quantitative Finance Collector, and kindly contributed to R-bloggers)

Classes (S4) of commonly used copulas including elliptical (normal and t), Archimedean (Clayton, Gumbel, Frank, and Ali-Mikhail-Haq), extreme value (Husler-Reiss and Galambos), and other families (Plackett and Farlie-Gumbel-Morgenstern). Methods for density, distribution, random number generation, bivariate dependence measures, perspective and contour plots. Functions for fitting copula models. Independence tests among random variables and random vectors. Serial independence tests for univariate and multivariate continuous time series. Goodness-of-fit tests for copulas based on multipliers and on the parametric bootstrap.

R package can be downloaded at
Tags –
Read the full post at Multivariate dependence with copulas.

To leave a comment for the author, please follow the link and comment on their blog: Quantitative Finance Collector. offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...

If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.


Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)