R Fortran using rejection sampling in rtmvnorm() gives error I'm sampling from a multivariate normal truncated distribution using rtmvnorm() function from tmvtnorm package in R. Using the rejection algorithm method, I can check the acceptance rate using pmvnorm(), as described in the article by Wilhelm & Manjunath (2010) who explain the package.
Here is an example of my code:
# creating covariance matrix using different random correlations 
n = 8    
c <- c(rnorm((n*(n-1))/2, mean = .1, sd = 1))
sigma <- diag(8)
sigma[lower.tri(sigma, diag = F)] <- c
sigma <- forceSymmetric(sigma, "L") # creating symmetric correlation matrix
sigma <- sigma * (sqrt(1.5) * sqrt(1.5)) #creating covariance matrix from correlation matrix
sigma <- as.matrix(nearPD(sigma)$mat) #make covariance matrix positive definite

#random sampling multivariate truncated distribution using sigma
mean <- rnorm(n, 6.5, 1.5)    
t <- rtmvnorm(10, mean = mean, sigma = sigma, lower = c(rep(1,n)), upper = c(rep(10,n)),
              algorithm = "rejection")
alpha <- pmvnorm(lower = c(rep(1,n)), upper = c(rep(10,n)), mean = mean, sigma = sigma)
[1] 0.6900399
attr(,"error")
[1] 0.001841024
attr(,"msg")
[1] "Completion with error > abseps"

Now, my acceptance rate .69 is alright, and increases if I simulate a covariance matrix that has an higher mean (instead of .1). However, the accompanied error message indicates that the completion is with error > abseps. I found that this means my error is higher than the absolute error tolerance of .001. I was wondering if someone knows what this error tolerance indicates exactly? 
I've tried looking up the codes but it gets me to mtv() from mvtnorm package in R which refers to a function written in Fortran, MVTDST, http://www.math.wsu.edu/faculty/genz/software/fort77/mvtdstpack.f. As I am unfamiliar with this language. I'm not quite sure what produces the message and how bad it would be to lower the error or to ignore the message. 
 A: For what it is worth, one can get a Normal Completion message in some cases by increasing the maxpts -- which can be read about in ?mvtnorm::GenzBretz.  The default for maxpts is 25000.  Below is the OP code with library() and set.seed() statements to make it reproducible and then a demonstration of increasing the maxpts from 25000 to 10*25000 in the alpha2 call.  The expected answers are commented out below the pmvnorm() calls:
library(tmvtnorm)
library( mvtnorm)

set.seed(424242)

# creating covariance matrix using different random correlations 
n = 8    
c <- c(rnorm((n*(n-1))/2, mean = .1, sd = 1))
sigma <- diag(8)
sigma[lower.tri(sigma, diag = F)] <- c
sigma <- forceSymmetric(sigma, "L") # creating symmetric correlation matrix
sigma <- sigma * (sqrt(1.5) * sqrt(1.5)) #creating covariance matrix from correlation matrix
sigma <- as.matrix(nearPD(sigma)$mat) #make covariance matrix positive definite

#random sampling multivariate truncated distribution using sigma
mean <- rnorm(n, 6.5, 1.5)    
t <- rtmvnorm(10, mean = mean, sigma = sigma, lower = c(rep(1,n)), upper = c(rep(10,n)),
              algorithm = "rejection")
alpha <- pmvnorm(lower = c(rep(1,n)), upper = c(rep(10,n)), mean = mean, sigma = sigma)
alpha
# [1] 0.7572689
# attr(,"error")
# [1] 0.002857951
# attr(,"msg")
# [1] "Completion with error > abseps"


## increase maxpts
alpha2 <- pmvnorm(lower = c(rep(1,n)), upper = c(rep(10,n)), mean = mean, sigma = sigma, 
                  maxpts=10*25000)
alpha2
# [1] 0.7569266
# attr(,"error")
# [1] 0.0007923042
# attr(,"msg")
# [1] "Normal Completion"

