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### R code from vignette source 'MVT_Rnews.Rnw'
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### code chunk number 1: prelim
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set.seed(290875)
### options(width=60, prompt="R> ")
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### code chunk number 2: smallex
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library("mvtnorm")
m <- 3
sigma <- diag(3)
sigma[2,1] <- 3/5
sigma[3,1] <- 1/3
sigma[3,2] <- 11/15
(prb <- pmvnorm(lower = rep(-Inf, m), upper = c(1, 4, 2),
mean = rep(0, m),
corr = sigma) ### only lower triangular
### part used
)
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### code chunk number 3: cats
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n <- c(26, 24, 20, 33, 32)
V <- diag(1/n)
df <- sum(n) - length(n)
C <- matrix(c( 1, 1, 1, 0, 0,
-1, 0, 0, 1, 0,
0,-1, 0, 0, 1,
0, 0, 0,-1,-1,
0, 0,-1, 0 ,0),
ncol = length(n))
### covariance matrix
cv <- tcrossprod(C %*% V, C)
### correlation matrix
cr <- cov2cor(cv)
delta <- rep(0, 5)
(qnt <- qmvt(0.95, df = df, delta = delta, corr = cr,
abseps = 0.0001, maxpts = 100000, tail = "both"))
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