similar to: Log likelihood estimation using bivariate archimedean copula

Hi everybody, I try to simulate random numbers from a trivariate nested Archimedean copula. My aim is to correlate two processes with, e.g. theta2, as the so called child pair and then to correlate these two processes with a third one with theta1 (parent). This "figure" tries to capture what I am explaining theta1 theta2

I am having the following error in my function function(theta,reqdIRR) { theta1<-theta[1] theta2<-theta[2] n<-length(reqdIRR) constant<- n*(theta1+theta2) sum1<-lapply(reqdIRR*exp(theta1),FUN = sum) sum2<-lapply(exp(theta2 - reqdIRR*exp(theta1)),FUN = sum) sum = sum1 + sum2 log.fcn = constant - as.numeric(sum) result = - log.fcn return(result) } *error :

Hello, I am a new user of R (2.13.1), my operational system is Windows Vista. I have a problem with the attached file SFEVaRHAC.r, calculating the VAR of a Gumbel copula, based on the attached GumHAC_VaR_PL_w250_n1000_s2500.txt 1. I had a Error in file(file, "rt") : cannot open the connection message. I solved it by reading a post in nabble to use setwd(choose.dir()) and

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

>>>>> 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;

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]]

I got some R code that I don't understand. Question as comment in code //where is t comming from, what is phi inverse rAC <- function(name, n, d, theta){ #generic function for Archimedean copula simulation illegalpar <- switch(name, clayton = (theta < 0), gumbel = (theta < 1), frank = (theta < 0), BB9 = ((theta[1] < 1) | (theta[2] < 0)), GIG = ((theta[2] < 0) |

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 All, I'm now looking for R-code on how to find the Goodness of Fits for Archimedean Copulas. If anyone have a guide for this problems please lets me know. Your prompt action is much appreciated. Regards, Ummul [[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

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

"Jenny Stadt" <jennystadt at yahoo.ca> asked: > > I am struggling in a bivariate Weibull distribution although I > searched R-Site-Help and found suggestion with Copula. Seems the > maximum likelihood estimate is beyond what I can understand. > > My case is: given two known marginal distribution (both are Weibull), > and the correlation between them. How can I

Hello, I have a bigger problem in calculating the Maximum Likelihood Estimator regarding the degree of freedom of a multivariate skew-t copula. First of all I would like to describe what this is all about, so that you can understand my problem: I have 2 time series with more than 3000 entries each. I would like to calculate a multivariate skew-t Copula that fits this time series. Notice:

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

Hello, Hela wrote : My problem in a few words is as folow: I used the fCopulae packages because i have 2 series which are already transformed in the uniform domain (the space of the copulas functions) and i estimated with type archmList() from 1 to 22, but i don't know their names:for exemple the type=4 is the Gumbel Copula...and for the others i can't have any idea about how can i find

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

Hi, I found this document, but it concerns S+. If it could interest you'll see: http://faculty.washington.edu/ezivot/book/QuanCopula.pdf Cordially Vito You wrote: Dear R: Is there a function or a reference to simulate Gumbel copulas, please? Thanks in advance! Sincerely, Erin Hodgess mailto: hodgess at gator.uhd.edu R version 2.0.1 windows ===== Diventare costruttori di soluzioni

Dear R: Is there a function or a reference to simulate Gumbel copulas, please? Thanks in advance! Sincerely, Erin Hodgess mailto: hodgess at gator.uhd.edu R version 2.0.1 windows

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

Hi, I want to run a quantile regression (Y=a+bX+e) using normal and t copula for my dissertation. I 've read the documentation of "copula" and "copBasic". However, I still have difficulty to deal with my data. Details are as following: I've already loaded xls data into r using "XLConnect" package. excel.file<-file.path("Q:/dailyvstoxx.xls")