similar to: calculation of probability values from multivariate normal densities

-------------- next part -------------- An embedded message was scrubbed... From: Barbara Cegielska <barceg at ibch.poznan.pl> Subject: loading SPOT file Date: Wed, 06 May 2009 16:48:35 +0200 Size: 1151 URL: <https://stat.ethz.ch/pipermail/r-help/attachments/20090506/e35e3f7e/attachment-0002.eml>

Package mvtnorm provides dmvnorm, pmvnorm that can be used to compute Pr(X=x,Y=y) and Pr(X<x,Y<y) for a bivariate normal. Are there functions that would compute Pr(X<x,Y=y)? I'm currently using "integrate" with dmvnorm but it is too slow.

I would like to load ApoAI.RData. During the operation of reading this data an error occurs. There is also a problem with STF file. > library (limma) > load("ApoAI.RData") Warning message: 'RG' looks like a pre-2.4.0 S4 object: please recreate it > objects() [1] "RG" > names(RG) [1] "R" "G" "Rb"

Dear list members I need a function that calculates the bivariate normal distribution for each observation. It is part of a likelihood function and I have 1000's of cases. As I understand it I cannot use packages like "mvtnorm" because it requres a covariance matrix of the same dimension as the number of observations. Basically what I need is a function that takes as arguments a

Hi, Would you help me solve the following question? Thanks. Question: If I try to set the probability=0.05 and find the approximate x. (The answer should be somewhere between 2.1782 and 2.1783.) I write about this R program as follows but I don¡¦t know how to get the value of x which is between 2.1782 and 2.1783. library(mvtnorm) value<-array(1000) a<-array(1000)

Good point. Now this returns 0.04062184. Hmmm..... On Mon, Oct 2, 2017 at 6:30 PM, Hollie Johnson (PGR) < h.a.johnson at newcastle.ac.uk> wrote: > Hi Eric, > > > Thanks for having a look into this. I think you have a small typo... > > B <- matrix(x, nrow=3, byrow = TRUE) should read B <- matrix(y, nrow=3, > byrow = TRUE) > > > Regards, Hollie >

Currently doing some work on local maxima on a random field and have encountered an issue with the Miwa algorithm used with the pmvnorm function in the mvtnorm R package. Based on recommendations by Mi et al., we ran the mvtnorm package using the Miwa algorithm, since we have a maximum of 4 dimensions with non-singular matrices. However, running the estimation procedure in this way, we obtained

Hi there, pmvnorm(lo=c(-Inf,-Inf), up=c(Inf,Inf), mean=c(0,0) ) should give me "1", right? But it doens't - it giver me "0". Would someone help me, please? [[alternative HTML version deleted]]

Hi, I would like to interface a C code into R. Is it possible to use in the C code, functions from a R package (for instance, to use pmvnorm within loops in the C code and to call the result in a R function)? Nathalie

Hello there! My operating system is Windows XP, my version of R is the latest (R-2.5.0). Recently I have downloaded the package "mvtnorm" and a problem with the command "pmvnorm" occured. Trying to enter the lines ... A <- diag(3) A[1,2] <-0.5 A[1,3] <- 0.25 A[2,3] <- 0.5 pvmnorm(lower=c(-Inf,-Inf,-Inf), upper=c(2,2,2),mean = c(0,0,0), corr=A) I got the following

Rather specialized. As this appears to be primarily a statistical, not an R programming question, you may do better posting on a statistical site like http://stats.stackexchange.com/ if you don't get a satisfactory reply here . Alternativey, if you think this is a package bug, perhaps contact the package maintainer directly, as (s)he may not monitor this list. -- Bert Bert Gunter

Hi, can anyone help me with the following code? Thanks! library(mvtnorm) f2 <- function(n, rho) { var <- matrix(c(1,rho,rho,1), nrow=2, ncol=2, byrow=T) beta <- seq(0, 1, length.out=n+1) alpha <- sort (sapply(1-beta, qnorm)) x <- array(0, dim=c(n, n)) for (s in 1:n) { for (t in 1:n){ if (s>=t) x[s,t] <- pmvnorm(lower=c(alpha[s],

hello, I'm trying to improve the speed of my calculation but didn't get to a satisfying result. It's about the numerical Integration of a bivariate normal distribution. The code I'm currently using x <- qnorm(seq(.Machine$double.xmin,c(1-2*.Machine$double.eps),by=0.01), mean=0,sd=1) rho <- 0.5 integral <- function(rho,x1){

Dear R Users I am maximizing a user defined log likelihood function. It includes variance parameter (sigma). I used R function optim with BFGS maximization method. However, it stops before the solution saying ?sqrt(sigma): NaNs produced? Could anybody know a proper transformation for sigma which can be passed in the function? For the correlation parameter I used Fishers? transformation so it

Hi all, Can anyone tell me what the following error message means? " Error in mvt(lower = lower, upper = upper, df = 0, corr = corr, delta = mean, : NA/NaN/Inf in foreign function call (arg 6)" It was generated when I used the 'pmvnorm' function in the 'mvtnorm' package. Thanks a lot. Yonghai Li

I am trying calculate a probability using numerical integration. The first program I ran spit out an answer in a very short time. The program is below: ## START PROGRAM trial <- function(input) { pmvnorm(lower = c(0,0), upper = c(2, 2), mean = input, sigma = matrix(c(.1, 0, 0, .1), nrow = 2, ncol = 2, byrow = FALSE)) } require(mvtnorm) require(adapt) bottomB <- -5*sqrt(.1) topB <-

I'm trying to obtain numerical derivative of a probability computed with mvtnorm with respect to its parameters using grad() and jacobian() from NumDeriv. To simplify the matter, here is an example: PP1 <- function(p){ thetac <- p thetae <- 0.323340333 thetab <- -0.280970036 thetao <- 0.770768082 ssigma <- diag(4) ssigma[1,2] <- 0.229502120

Dear all, I am trying to calculate certain critical values from bivariate normal distribution (please see the function below). m <- 10 rho <- 0.1 k <- 2 alpha <- 0.05 ## calculate critical constants cc_z <- numeric(m) var <- matrix(c(1,rho,rho,1), nrow=2, ncol=2, byrow=T) for (i in 1:m){ if (i <= k) {cc_z[i] <- qmvnorm((k*(k-1))/(m*(m-1))*alpha,

I'm trying to implement a recursive function using integrate, and I suspect I need a Vectorize somewhere, but I can't suss it out. Any help would be appreciated. I've tried traceback() and various debugging ideas to no avail (most likely due to my inexperience with these tools.) Here's what I have. Nk <- function(m, C) { if (length(m) > 1) { rho <- C[1, -1]

Dear users, does any one have a code (S or R) to compute the binormal distribution (or the upper its quadrant area) other than the pmvnorm. Thanks -- Nabil Channouf etudiant en Ph.D. Bureau 3733 Departement d'Informatique et de Recherche Operationnelle (D.I.R.O.) Universite de Montreal, C.P. 6128, succ. Centre-Ville, Montreal, H3C 3J7 Tel.: (514) 343-6111, poste 1796 Fax.: (514) 343-5834