similar to: Help with optim function in R, please?

Hi all, I'm trying to define and log-likelihood function to work with MLE. There will be parameters like mu_i, sigma_i, tau_i, ro_i, for i between 1 to 24. Instead of listing all the parameters, one by one in the function definition, is there a neat way to do it in R ? The example is as follows: ll<- function(mu1=-0.5,b=1.2,tau_1=0.5,sigma_1=0.5,ro_1=0.7) { if (tau1>0 &&

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)) >

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

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

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! 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

>>>>> 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 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:

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

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

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

Greetings, I'm interested in generating data from various bivariate or mulitivariate distributions (e.g. gamma, t, etc), where I can specify the parameter values, including the correlations among the variables. I haven't been able to dig anything up on the faq, but I probably missed something. A nudge in the right direction would be appreciated. David --