similar to: Copula in R 2.4.0

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

Hi all, Many thank in advance for helping me.? I tried to fit Expectation Maximization algorithm for mixture data. I must used one of numerical method to maximize my function. I built my code but I do not know how to make the optim function run over a different value of the parameters.? That is, For E-step I need to get the value of mixture weights based on the current (initial) values of

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)) >

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")

Hello R users, A beginners question which I could not find the answer to in earler posts. My thought process: Here "z" is a 119 x 15 data matrix Step 1: start at column one, bind every column with column 1 Step2: use the new matrix, "test", in the fitCopula package Step3: store each result in myfit, bind each result to "answer" Step4: return "answer"

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"?

>>>>> 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 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

Can someone help interprete the error message below? i was trying to load the package "copula" from the R command prompt. > Error in loadNamespace(package, c(which.lib.loc, lib.loc), keep.source = keep.source) : in 'copula' methods specified for export, but none defined: show, summary, persp, contour Error: package/namespace load failed for 'copula' Thanks, Dominique

Dear r-users, Is there any command in R allowing to evaluate a double integral? for instance let say I want to evaluate the following integral: integrate[lo=(0,1),up=(2,3)] f(x,y)=x^2+y^2 where lo is the vector of lower bounds and up that of upper bounds. I thaught the function "adapt" would work but it did not. Many thanks, Dominique K.

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

-- 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

Dear helpeRs, I seem to be a little bit confused on the result I am getting from the few codes below: > u=v=seq(0,1,length=30) > u [1] 0.00000000 0.03448276 0.06896552 0.10344828 0.13793103 0.17241379 [7] 0.20689655 0.24137931 0.27586207 0.31034483 0.34482759 0.37931034 [13] 0.41379310 0.44827586 0.48275862 0.51724138 0.55172414 0.58620690 [19] 0.62068966 0.65517241 0.68965517 0.72413793

Hi, I want to run a quantile regression (Y=a+bX+e) using normal and t copula for my dissertation. I 've read the documentation of "copula" and "copBasic". However, I still have difficulty to deal with my data. Details are as following: I've already loaded xls data into r using "XLConnect" package. excel.file<-file.path("Q:/dailyvstoxx.xls")

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

I'm a new user of R and a novice user in copula R package. I want to fit 3-dimensional t copula for my trivariate data. So I used the command t.cop <- tCopula(c(0.785,0.283,0.613),dim=3,dispstr="un",df=6,df.fixed = TRUE) where c(0.785,0.283,0.613) is the correlation pattern of my data with 0.785 pearson correlation between variable 1-2, 0.283 correlation between 1-3 and 0.613

Hi all, I need to test gof of 3-dimensional t copula for my trivariate observed data set. So I used the command t.cop <- tCopula(c(0.785,0.283,0.613),dim=3,dispstr="un",df=6,df.fixed = TRUE) where c(0.785,0.283,0.613) is the correlation pattern of my data with 0.785 pearson correlation between variable 1-2, 0.283 correlation between 1-3 and 0.613 is the correlation between variable

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