similar to: how to run copula-based quantile regression

We (the lme4 authors) are having a problem with doing a proper deep copy of a reference class object in recent versions of R-devel with the LAZY_DUPLICATE_OK flag in src/main/bind.c enabled. Apologies in advance for any improper terminology. TL;DR Is there an elegant way to force non-lazy/deep copying in our case? Is anyone else using reference classes with a field that is an external pointer?

Hi all, Has anyone used the qua.regressCOP2 function from the copBasic package??? The default copula function used in this function is plackett copula and I wanted to use archimedean copula. Attached below is my code: mycop<-frankCopula V=seq(0.001,0.99,by=0.000217) R<-qua.regressCOP2(0.25,V,cop=mycop,para=c(3.504)) And this is the error I get: Warning messages: 1: In

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Gracias a todos por las recomendaciones. Ya me he puesto en contacto con el autor y le explicado donde esta el error. Es tan fácil como que han cambiado la estructura de los objetos tipos lmer desde la versión 2.15.3 con lo que su paquete dejo de funcionar. Por suerte la nueva estructura conserva por lo menos la parte necesaria para hacer sus funciones. Se localizar el fallo y como arreglarlo, lo

Hace unos meses os escribir para comunicaros que había un fallo en esta función. Como os prometí os comento la respuesta por si alguno está interesado en utilizar el paquete LMERconvenientsfucntions Dear Javier, The package has been updated and should work for you fine now. Note that function mcp.fnc does not return the fourth plot (dffits) anymore. We still have to figure out a way to compute

Hi R-users, Where can I find the code for asymmetric t-copula in R? Thank you for any help given. [[alternative HTML version deleted]]

Hi, I would like to implement the empirical copula in R, does anyone know if it is included in a package? I know it is not in the "Copula" package. This one only includes a gof-test based on the empirical copula process. Thanks for your help! Gregor -- View this message in context: http://www.nabble.com/Empirical-copula-in-R-tf4018319.html#a11412335 Sent from the R help mailing list

I'm a new user of R and a novice user in copula R package. I want to fit 3-dimensional t copula for my trivariate data. So I used the command t.cop <- tCopula(c(0.785,0.283,0.613),dim=3,dispstr="un",df=6,df.fixed = TRUE) where c(0.785,0.283,0.613) is the correlation pattern of my data with 0.785 pearson correlation between variable 1-2, 0.283 correlation between 1-3 and 0.613

Hi, I'd like to know why using the program "R" I can't add a number of margins> 3, I have a problem with the graphics. Post here my script: > myCop.norm <- ellipCopula(family = "normal", dim = 3, param = 0.4) > myMvd <- mvdc(copula = myCop.norm, margins = c("norm", "norm","norm"), > paramMargins = list(list(mean = 0, sd

Hi, I'm a new user of R. I'm using package copula implemented in R. I want to know how to test goodness of fit of student's t copula for 3 dimensional cases using real world data. In manual gof test has been performed on the copula families generated from rcopula function that i understood as random data generated from copula? How to perform the test with real/observed data matrix.

Hello R-Team, I am trying to construct a Copula from a multivariate Gamma distribution with its marginals gamma-distributed. The multivariate Gamma should be able to contain a correlation coeficient or matrix. I have studied the book "Continuous Multivariate Distributions vol.I Models and applications" by Johnson & Kotz & Balakrishnan but what I constructed doesn't really

Dear users I am reposting this and hope it will be accepted this time. I am using copula package to fit my bivariate data and simulation. As explained in package documentation we can use our own data distribution to feed on copula as long as we have d, p and q (pdf, cdf and quantile) functions are available. Hence my code for those are: # Make the functions for data distribution

Hello Has anybody implemented a copula correlation in R in order to correlate between two non-normally distributed time series. Thanks Sean

Hi, I am trying to fit t copula to some data, and I am using the following function in the library(QRMlib). Udatac <- apply(datac, 2, edf,adjust=1) tcopulac <- fit.tcopula.rank(Udatac) But the error message come out "Error in fit.tcopula.rank(Udatac) : Non p.s.d. covariance matrix" Could anyone give me some advice? In fact, I am not sure what the "adjust=1" is used for.

Hi all, I am trying to build a copula model using the Gumbel Copula and I have two marginal distributions.I know the marginal parameters by using the fitdistr() and optim().The problem is I dont know my copula parameter. I am getting a bit confused of how shall I go about it.I read the previous threads where the query was to estimate all the parameters.How shall I define my log-likelihood

Dear All, I'm now working on Archimedean copulas and try to test the goodness of fit. Which packages I should use? I have Clayton copula with parameter (5.35) and Frank (19.5). I found this build function wrote by Yan and Ivan via R Packages, but I'm not sure the matrix for x? Please advice. e.g gofCopula(claytonCopula(1),x) Thank you Regards, Fayyad [[alternative HTML version

How can i calculate the discrete L2 distance between the empirical copula and the estimated one. -- View this message in context: http://www.nabble.com/Goodness-of-fit-tests-for-copula-tp17779318p17779318.html Sent from the R help mailing list archive at Nabble.com.

Hi R-users, Where can I find the code for asymmetric t-copula in R? Thank you for any help given. [[alternative HTML version deleted]]

Somebody know what is the package in which I can find the association measures (like Kendall's Tau and Spearman's Rho) for a copula object (bivariate copulas)?? Thanks a lot. Marta Di Lascio __________________________________________________ [[alternative HTML version deleted]]

Dear all, I just came to R a few days ago. Now I have a problem that I have two correlated variables and want to first fit a Gaussian copula, then sample it to generate simulated variables. I have spent last two days looking at R archive and copula help file but couldn't find what I need. If my understanding is correct, all examples I saw work in this way: a man-made copula -> simulated