similar to: Kendall for Copula

Hi r-users, I try to fit the t copula using the gamma marginals.  But I got error message which I don't really understand. Thank you for any help given. myCop.t <- ellipCopula(family = "t", dim = 2, dispstr = "toep", param = 0.5, df = 8) myCop.t myMvd <- mvdc(copula = myCop.t, margins = c("gamma", "gamma"), paramMargins = list(list(mean = 0, sd

Colleagues, I ran some nonparametric regressions in R (run in RedHat Linux), then a colleague repeated the analyses in SAS. When we obtained different results, I tested S-Plus (same Linux box). And, got yet different results. I replicated the results with a small dataset: DATA: 37.5 23 37.5 13 25 16 25 12 100 15 12.5 19 50 20 100 13 100 10 100 10 100 16 50 10 87.5

Dear R maintainers, R is great. Now that I have that out of the way, I believe I have encountered a bug, or at least an inconsistency, in how Spearman and Kendall rank correlations are handled. Specifically, cor() and cor.test() do not produce the same answer when the data contain NAs. cor() treats the NAs as data, while cor.test() eliminates them. The option use="complete.obs" has

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

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

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

Full_Name: Dirk Koschuetzki Version: 2.1.1 OS: source code Submission from: (NULL) (194.94.136.34) Hello, >From the source code (R-2.1.1, file: .../R-2.1.1/src/library/stats/R/) ****************************** cor.test.default <- function(x, y, alternative = c("two.sided", "less", "greater"), method = c("pearson", "kendall",

Hi r-users,   I really need help in fitting the t-copula.  I try to reproduce the example given by Jun Yan in “Enjoy the joy of copula” but I’m not sure how to correct the error based on the error message.  I tried so many ways but still could not get it working.   loglik.marg <- function(b, x) sum(dgamma(x, shape = b[1], scale = b[2], log = TRUE))   ctrl <- list(fnscale = -1)   #dat <-

Hi r-users, I really need help in fitting the t-copula. I try to reproduce the example given by Jun Yan in "Enjoy the joy of copula" but I'm not sure how to correct the error based on the error message. I tried so many ways but still could not get it working. loglik.marg <- function(b, x) sum(dgamma(x, shape = b[1], scale = b[2], log = TRUE)) ctrl <- list(fnscale

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

Full_Name: Marek Ancukiewicz Version: 2.10.1 OS: Linux Submission from: (NULL) (74.0.49.2) Both cor() and cor.test() incorrectly handle ordered variables with method="kendall", cor() incorrectly handles ordered variables for method="spearman" (method="person" always works correctly, while method="spearman" works for cor.test, but not for cor()). In

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 would like to do a PCA with dudi.pca or PCA, but also with the use of Spearman or Kendall correlations Is it possible ? Otherwise, how can I do, according to you ? Thanking you in advance Eric Bourgade RTE France [[alternative HTML version deleted]]

"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

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 R users, I was trying to find a library for the Chi-plot and Kendall plot, as described in the paper "Everything you always wanted to know about Copula Modeling but you were afraid to ask", but unsuccessfully. I was wondering if anyone have already implemented these 2 functions in R? Many thanks in advance, Nan

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 all, I would like to ask a question related to Kendall package. I ran Kendall (x,y) and saw the results. But I am not sure which tau values R reported. I have ties in my data set, so I want tau-b. Can anybody tell how Kendall package is calculating tau values? I have looked at the package PDF, but I could not find any useful information. As long as I see from the following link, there

> library(Kendall) > Kendall(1:3,1:3) WARNING: Error exit, tauk2. IFAULT = 12 <<<<<< tau = 1, 2-sided pvalue =1 I believe Kendall tau is well-defined for this case and the reported value is correct; isn't it a bug to give a warning? (And if, e.g., the pvalue is not well-defined in this case, wouldn't it be better to return NA or NaN or something?) Also,

Hello, I am trying to do a fit a loglikelihood function with Multivariate distribution via copulas with fitMdvc. The problem is that it doesn't recognize that my beta is a vector of km parameter and when I try to run it it say that the length of my initial values is not the same as the parameter. Can somebody guide me where my mistake is. Thanks, Elisa. #################################