similar to: Copula calculation in R?

Hi, Is anybody using Copula package for fitting copulas to own data? I have two marginals Log Normal with (parameters 1.17 and 0.76) and Gamma ( 2.7 and 1.05) Which package I should use to fit Gumbel and Clayton Copulas? Thanks, fayyad [[alternative HTML version deleted]]

hi, first I want to say that I'm new here, and new with copula and R. That is the reason why I'm writing, if somebody can help me. I have to make an example of Copula. On internet I've found this forum and that copula can calculate with R. Can somebody help me with the thing how can I start and where can read about these stuffs. Thank to all who can help! -- View this message

Thanks Dimitris!!! That's much clearer now. Still have a lot of work to do this weekend to understand every bit but your code will prove very useful. Cheers, Aziz -----Original Message----- From: Dimitrios Rizopoulos [mailto:Dimitris.Rizopoulos at med.kuleuven.be] Sent: May 12, 2006 4:35 PM To: Chaouch, Aziz Subject: RE: [R] Maximum likelihood estimate of bivariate

Dear r list, I posted this on the S list last week since i'm using some of the FinMetrics functions on copula. Knowing there is a copula package in R, I figure this would be an appropriate forum to ask this question. I want to model inverse relationship between two (non-normal, non-symmetric) marginals with the gumbel copula, or with any copula. Say, x is lognormal and y is norm. Since

Hi, Is anybody using Copula package for fitting copulas to own datas? I always got this message: Error in qnorm(p, mean, sd, lower.tail, log.p) : Non-numeric argument to mathematical function thanks, Psl _______________________________________________________________ Ossza meg bar?taival f?nyk?pen meg?r?k?tett ?lm?nyeit. http:\\fototar.t-online.hu

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

Can anyone advise me on some pratical papers or books On Gaussian Copulas? Anything in the genre of Copulas Dummies Would be a help. As simpe, and approachable with minimal pedantic style. Thanks, Neil -------------------------------------------------------- This information is being sent at the recipient's reques...{{dropped:16}}

Hi, If I use the levelplot function of the lattice library, I always see small "squares" in the plot. They indicate the region for which the same color is used. If you have a levelplot of a function which is evaluated at 25x25 equally-spaced points you obtain 26 squares in x and 26 squares in y direction. That does not bother too much (but still bothers somehow...), but if you

I am trying to make a loglikelihood function using copulas. I am trying to use mvdc to find the density function. When I run this I got the error that the pdf and cdf of my function tobit doesn't exist. Can somebody guide me where my mistake is? dtobit <- function(beta,sigma, x, y) {ifelse(y>0, dnorm(y,x%*%beta, sigma),(1-pnorm((x%*%beta)/sigma)))} ptobit <- function(beta,sigma, x,

Hi all, I am going to sample two variables from two exponential distributions, but I want to specify a covariance structure between these two variables. Is there any way to do it in R? Or is there a "Multivariate Exponential" thing corresponding to the multivariate normal? Thanks in advance. Sincerely, Yanwei Zhang Department of Actuarial Research and Modeling Munich Re America Tel:

Hello! I am trying to fit a copula to some data in R and I get the error mentioned above. This is the code for a reproducible example - library(copula) data = matrix(data=runif(600),nrow=200,ncol=3) data[,2] = 2*data[,1] data[,3] = 3*data[,1] fr_cop = frankCopula(dim=3) fit_fr_cop = fitCopula(fr_cop,pobs(data),method = "mpl") #Error Here The error says : Error in fitCopula.ml(copula, u

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

HI Every one Could some one provide me definitions of following bivariate distributions gamma, exponencial, Weibull, half-normal , Rayleigh, Erlang,chi-square thanks A.S. Qureshi

>>>>> Soumen Banerjee <soumen08 at gmail.com> >>>>> on Sat, 21 Apr 2018 17:22:56 +0800 writes: > Hello! I am trying to fit a copula to some data in R and > I get the error mentioned above. This is the code for a > reproducible example - (not really reproducible: You did not set the random seed, so the data is different every time;

Dear I estimate a sample selection model using the Clayton copula and Burr and Gaussian marginal. I need to derive ther Kendall'sw tau from the concordance coefficient by integration. I came across a way to do that in R long time ago but cannot find it again. Can somewone tell me what to read and what to use? Thank you. Steven Yen

Hello I am writing to you regarding your interest in Copula/copulae and it?s usage. I am currently studying Copula for my Master thesis and also therefore have a large interest in it. Now I am looking for information regarding copula as well as Copula and "R". Code, information how to calculate or anything would be appreciated! Since there seem to be little information regarding

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

Hi R-users, I would like to use the copula package.? I? the package plus the mvtnorm and try to run the example given, but I got the following message: install.packages(repos=NULL,pkgs="c:\\Tinn-R\\copula_0.8-3.zip") norm.cop <- normalCopula(c(0.5, 0.6, 0.7), dim = 3, dispstr = "un") t.cop <- tCopula(c(0.5, 0.3), dim = 3, dispstr = "toep", df = 2, df.fixed =

Dear R-helper, Is there any thing that I am doing wrong in the following codes: > norm.cop <- normalCopula(0.5) > persp(norm.cop, dcopula) The last command produces what follows Error in persp(x, y, z, xlim, ylim, zlim, theta, phi, r, d, scale, expand, : invalid 'x' argument In addition: Warning messages: 1: no non-missing arguments to min; returning Inf 2: no

Hey all, I'm trying to construct a 7-dimensional normal copula using the copula package. I'd like to supply as parameter a randomly generated correlation matrix (that I'll convert to a vector so I can feed it to the normalCopula function). What order do the pairwise correlations inside that vector have to be in? In other words: What does the normalCopula function "expect"?