similar to: R and Copula

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

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,

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

Hello Anyone that now of any function in R that can calculate copulas? Or if anyone have any code avaible I would be more than interested. Thank you in advance /Thomas ______________________________________________ R-help at stat.math.ethz.ch mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help

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

>>>>> 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 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

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

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"?

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]]

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

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

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

Hello everybody, I have a big problem that I do not manage to solve ! I will be very grateful if you can solve this ! I want to fit a t Copula with the copula package : > student.cop <- ellipCopula("t", param = c(0.5, 0.6, 0.7), dim = 3, dispstr = "un",df=5) > x<-rcopula(student.cop,1000) > fit <- fitCopula(x, student.cop, c(0.5,0.5,0.5,5)) And there is an

Hi all, I have this data set: ## Empirical copula ## dt1 = ranking ## dt2 = observed uniform data associated with the ranking   Sample data, > dt1         S_i   R_i  [1,]   7.0  10.0  [2,] 232.5 440.5  [3,] 143.0 141.5  [4,] 272.5 222.0  [5,]  46.0  34.0  [6,] 527.0 483.0  [7,] 420.5 563.5  [8,]  23.5  16.5  [9,]  56.5  68.5 [10,] 341.5 382.5   > dt2       unisk1 unisk2  [1,]  0.008  0.010

I need to fit a t copula with fixed degree of freedom let's say 4. I do not want to estimate the dof together with correlation matrix optimally. Instead fix the dof to 4 and only estimate the correlation matrix in the optimization routine. Is anyone aware of such estimation method in R. The packages and functions that I know of can't do this estimation. I searched online but