similar to: Copula package - normalCopula() param order

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 =

>>>>> 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;

Hola, Quiero saber si es posible programar una cópula donde las funciones marginales son multivariantes, siguiendo el esquema del package ''Copula''. Es decir, Copula(F(x,y), G(w,z))) En el caso de funciones marginales univariantes, un ejemplo de la normal multivariante quedaria de la siguiente forma,

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

I am using curve3d in the emdbook package to graph a gaussian copula density function generated via the copula package. Unfortunately, it appears that emdbook masks dmvnorm from the package mvtnorm in a way that prohibits copula from generating the gaussian copula. (Sounds very confusing!) For example, > library(copula) > f<-function(x,y) dcopula(normalCopula(0),c(x,y)) >

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

Dear R helper, does anyone have an idea on why R.2.4.0 draws the surface for the two command lines below and the next time it renders the error message below for exactly the same command lines: > norm.cop <- normalCopula(0.5) > persp(norm.cop, dcopula) Error in ceiling(length.out) : Non-numeric argument to mathematical function. I will appreciate any help from anyone thanks, Dominique

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

is() does not catch parent S3 classes: > library(splines) > temp <- bs(1:99, df=5) > class(temp) [1] "bs" "basis" > is(temp, "basis") [1] FALSE In contrast, is() does catch parent S4 classes: > library(copula) > norm.cop <- ellipCopula("normal", param = c(0.5, 0.6, 0.7), + dim = 3, dispstr = "un")

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

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

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

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

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 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]]

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 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

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:

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

Hey all, I'm performing polynomial regression. I'm simulating x values using runif() and y values using a deterministic function of x and rnorm(). When I perform polynomial regression like this: fit_poly <- lm(y ~ poly(x,11,raw = TRUE)) I get some NA coefficients. I think this is due to the high correlation between say x and x^2 if x is distributed uniformly on the unit interval