Calculates the Multivariate Normal Distribution with Product Correlation Structure published by Charles Dunnett, Algorithm AS 251.1 Appl.Statist. (1989), Vol.38, No.3, doi:10.2307/2347754 .
Usage
as251StudentT(
lower,
upper,
sigma,
...,
df,
eps = 1e-06,
errorControl = c("strict", "halvingIntervals"),
intervalSimpsonsRule = 0
)Arguments
- lower
Lower limits of integration. Array of N dimensions
- upper
Upper limits of integration. Array of N dimensions
- sigma
Values defining correlation structure. Array of N dimensions
- ...
Ensures that all arguments (starting from the "...") are to be named and that a warning will be displayed if unknown arguments are passed.
- df
Degrees of Freedom. Use 0 for infinite D.F.
- eps
desired accuracy. Defaults to 1e-06
- errorControl
error control. If set to 1, strict error control based on fourth derivative is used. If set to zero, error control based on halving intervals is used
- intervalSimpsonsRule
Interval width for Simpson's rule. Value of zero caused a default .24 to be used
Details
For a multivariate normal vector with correlation structure defined by rho(i,j) = bpd(i) * bpd(j), computes the probability that the vector falls in a rectangle in n-space with error less than eps.
This function calculates the bdp value from sigma, determines the right inf value and calls mvstud.