similar to: for loop problem

>>>>> 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;

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

Is anybody using the Copula package in R? The particular problem I'm facing is that R is not acknowledging the fitCopula command/function when I load the package and (try to) run something very simple: fit1 <- fitCopula(x1 = list(u11,u12,u13,u14,u15,u16,u17,u18), tCopula, optim.control = list(NULL), method = "BFGS") Anybody also using it, successfully or unsuccessfully?

I am using R 2.5.0 on windows XP and trying to fit copula. I see the following code works for some users, however my code crashes on the chol. Any suggestions? > mycop <- tCopula(param=0.5, dim=8, dispstr="ex", df=5) > x <- rcopula(mycop, 1000) > myfit <- fitCopula(x, mycop, c(0.6, 10), optim.control=list(trace=1), method="Nelder-Mead")

-- Hello, I am attempting to fit monthly stock returns to possible copula functions using the copula package in R. Below is my code (mat2 is a 2x119 matrix of the two stock returns): my.cop <- normalCopula(param=.3, dim = 2, dispstr = "un") myfit <- fitCopula(mat2,my.cop, start=.65, optim.control= list(NULL), method = "BFGS") myfit Unfortunately, I continue to receive

Hello everyone, Here is the setup. z is a 119 x 15 matrix, m_index is a 119 x 5 matrix What I am trying to do is return the results from fitCopula by sequentially binding all 15 columns of z to the first column of m_index, (cbind(z[,1],m_index[,1]),(cbind(z[,2],m_index[,1]), etc. Unfortunately, my code below only binds z[,1] and m_index[,1] and return the same result 14 times. Any ideas on

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 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

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 =

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"?

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

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 all, How can I convert factor like this: > str(repo) 'data.frame': 1000 obs. of 1 variable: $ AAA: Factor w/ 1000 levels "AAT","AAC",..: 1 2 3 4 5 6 7 8 9 10 ... > print(repo) AAA 1 AAA 2 AAT 3 AAC ... into to simple vector > str(new_repo) chr [1:100] "AAA" "AAT" "AAC" "AAG" "ATA" "ATT"...

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,

Dear all, I tried to find index in repo given a query with this: > repo <- c("AAA", "AAT", "AAC", "AAG", "ATA", "ATT") > qr <- c("AAC", "ATT", "ATT") > which(repo%in%qr) [1] 3 6 Note that the query contain repeating elements, yet the output of which only returns unique. How can I make it

I am new to R and am trying to specify a model for mixed model analysis. When I run the following model I get an error: AAT<- lmer(Y ~ S + A + (1|S:A/H), data=AT, REML=True) The error looks like this: Error in Spar_loc:`:` : NA/NaN argument In addition: Warning messages: 1: In model.matrix.default(mt, mf, contrasts) : variable 'Spar_loc' converted to a factor 2: In Spar_loc:`:` :

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

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")

Hi, How can I generate a random signal that's correlated with a given signal at a given correlation (say 0.7)? I've been looking at rmvnorm etc but don't seem to figure it out. Thanks ----- Yasir H. Kaheil Columbia University -- View this message in context: http://www.nabble.com/generating-a-random-signal-with-a-known-correlation-tp18932541p18932541.html Sent from the R help