Truncated Multivariate Student t Distribution
Computes the distribution function of the truncated multivariate t distribution
ptmvt(lowerx, upperx, mean = rep(0, length(lowerx)), sigma, df = 1, lower = rep(-Inf, length = length(mean)), upper = rep(Inf, length = length(mean)), maxpts = 25000, abseps = 0.001, releps = 0)
lowerx |
the vector of lower limits of length n. |
upperx |
the vector of upper limits of length n. |
mean |
the mean vector of length n. |
sigma |
the covariance matrix of dimension n. Either |
df |
Degrees of freedom parameter |
lower |
Vector of lower truncation points,
default is |
upper |
Vector of upper truncation points,
default is |
maxpts |
maximum number of function values as integer. |
abseps |
absolute error tolerance as double. |
releps |
relative error tolerance as double. |
The evaluated distribution function is returned with attributes
error |
estimated absolute error and |
msg |
status messages. |
Stefan Wilhelm <Stefan.Wilhelm@financial.com>
Geweke, J. F. (1991) Efficient simulation from the multivariate normal and Student-t distributions subject to linear constraints and the evaluation of constraint probabilities. http://www.biz.uiowa.edu/faculty/jgeweke/papers/paper47/paper47.pdf
Samuel Kotz, Saralees Nadarajah (2004). Multivariate t Distributions and Their Applications. Cambridge University Press
sigma <- matrix(c(5, 0.8, 0.8, 1), 2, 2) Fx <- ptmvt(lowerx=c(-1,-1), upperx=c(0.5,0), mean=c(0,0), sigma=sigma, df=3, lower=c(-1,-1), upper=c(1,1))
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