similar to: Simulation from a multivariate normal distribution

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Is there a command as "mat.or.vec(nr,nc)" to create an array that I must calculate with more cicle? [[alternative HTML version deleted]]

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Hello, I would like to simulate randomly from a multivariate normal distribution using a correlation matrix, rho. I do not have sigma. I have searched the help archive and the R documentation as well as doing a standard google search. What I have seen is that one can either use rmvnorm in the package: mvtnorm or mvrnorm in the package: MASS. I believe I read somewhere that the latter was

Sto imparando ora ad utilizzare R. Ho un problema: devo caricare i dati da un file xls creato da me, utilizzando la funzione "read.xls" produce il seguente errore: Errore in xls2csv(xls, sheet, verbose = verbose, ..., perl = perl) : Unable to read xls file 'indagineUSA.xls'. Errore in file.exists(tfn) : argomento 'file' non valido Cosa c'è che non va? La directory

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Dear everyone, I am having problem simulating multivariate data. Though I was able to simulate the data, but finding the variance-covariance matrix of simulated data did not give exact covariance matrix used in simulating the data. Unlike some other packages, like stata, using command "corr2data" will simulate data having the covariance matrix exactly with the specified covariance

For example, the correlation matrix is 3x3 and looks like 1 0.75 0 0 0 0.75 1 0 0 0 0 0 0 0 0 Can I write the code like this? p<- 3 # number of variables per observation N<- 10 # number of samples # define population correlation matrix sigma sigma<-matrix(0,p,p) #creates a px p matrix of 0 rank<-2 for (i in 1:rank){ for (j in 1:rank){ rho<-0.75

To whom it may concern, I try to simulate a non-normal multivariate distribution. The MASS package allows by mean of "mvrnorm" command to perform a multivariate normal simulation. Is there an equivalent command for an arbitrary multivariate distribution available in the R-language? Thank you in advance. Bernard Colin Colin Bernard Professeur titulaire D?partement de Math?matiques et

Dear?All, ? a few weeks ago I have posted a question on the R help listserv that?some of you have responded to with a great solution, would like to thank you for that? again.?I thought I would reach out to you with the issue I am trying to solve now. I have posted the question a few days ago, but probably it was not?clear enough, so I thought i try it again.?At times I have a multivariate example

Hi, I need to generate two normal variables with covariance matrix: 0.25, 0.20 0.20, 0.25 but I have no idea how to do that. Can anyone help me? Thanks, Joaquim ---------------------------------------------------------------------------- ---------- Joaquim J. S. Ramalho University of Bristol Department of Economics 8 Woodland Road Bristol BS8 1TN United Kingdom

Dear List: A few weeks ago I posted some questions regarding data simulation and received some very helpful comments, thank you. I have modified my code accordingly and have made some progress. However, I now am facing a new challenge along similar lines. I am attempting to simulate 250 datasets and then run the data through a linear model. I use rm() and gc() as I move along to clean up the

Hi, i'm not english and i'm not very familiar to R, and i'm asking if you can help me. I'm wondering how to create a multivariate normal an then repeat this for a sample of T=1000, and the save this result. Thank you very much for your helping -- View this message in context: http://r.789695.n4.nabble.com/Multivariate-Normal-and-loops-tp4633504.html Sent from the R help mailing

Hi All This might be something very trivial but I seem to miss something in the syntax or logic which makes me keep wandering around the problem without arriving at a solution. What I want to do is to simulate a sample data for performing cluster analysis. I tried to use x1= mvrnorm(10,rep(0.8,3),diag(3)) x2= mvrnorm(10,rep(0,3),diag(3)) x3= mvrnorm(10,rep(-0.5,3),diag(3)) x=rbind(x1,x2,x3)

I have to calculate the logreturn variance in the Heston model. How can I do? Do you know some function that calculates it? Thank you Barbara -- ________________________________________________________ Le informazioni contenute in questo messaggio di posta elettronica sono strettamente riservate e indirizzate esclusivamente al destinatario. Si prega di non leggere, fare copia, inoltrare a

¡Hola a todos! Estoy intentando muestrear de una normal multivariante donde hay dos grupos de variables que deben tener una relación "manipulable" entre sí pero ignoro cómo hacerlo. Les cuento, he intentado lo siguiente: # covarianzas del primer grupo de variables: Sigma_U <- matrix(c(.25, .2, .2, .25), ncol=2) # covarianzas del segundo grupo de variables: Sigma_W <- diag(2) #

Hello, I have a question about multivariate Shapiro-Wilks test. I tried to analyze if the data I have are multivariate normal, or how far they are from being multivariate normal. However, any time I did >mshapiro.test(mydata) I get the message: Error in solve.default(R %*% t(R), tol = 1e-18) : system is computationally singular: reciprocal condition number = 5.38814e-021 I tried

Please, I would like to know how to generate a truncated multivariate normal distribution k - dimensional, X ~ NT(mu, Sigma), where the elements of X to be non-negative (except the first), and the first dimension is strictly larger than zero. Example: X ~ NT_2(mu, Sigma), where mu=c(0.5, 0.5) and Sigma=c([120, 191], [191,154]), with X_1>0 and X_2>=0 Could anybody help