\name{algorithms} \alias{GenzBretz} \alias{Miwa} \alias{TVPACK} \title{ Choice of Algorithm and Hyper Parameters } \description{ Choose between three algorithms for evaluating normal distributions and define hyper parameters. } \usage{ GenzBretz(maxpts = 25000, abseps = 0.001, releps = 0) Miwa(steps = 128) TVPACK(abseps = 1e-6) } \arguments{ \item{maxpts}{ maximum number of function values as integer. The internal FORTRAN code always uses a minimum number depending on the dimension. (for example 752 for three-dimensional problems).} \item{abseps}{ absolute error tolerance as double. } \item{releps}{ relative error tolerance as double. } \item{steps}{ number of grid points to be evaluated. } } \details{ There are three algorithms available for evaluating normal probabilities: The default is the randomized Quasi-Monte-Carlo procedure by Genz (1992, 1993) and Genz and Bretz (2002) applicable to arbitrary covariance structures and dimensions up to 1000. For smaller dimensions (up to 20) and non-singular covariance matrices, the algorithm by Miwa et al. (2003) can be used as well. For two- and three-dimensional problems and semi-infinite integration region, \code{TVPACK} implements an interface to the methods described by Genz (2004). } \value{ An object of class \code{GenzBretz} or \code{Miwa} defining hyper parameters. } \references{ Genz, A. (1992). Numerical computation of multivariate normal probabilities. \emph{Journal of Computational and Graphical Statistics}, \bold{1}, 141--150. Genz, A. (1993). Comparison of methods for the computation of multivariate normal probabilities. \emph{Computing Science and Statistics}, \bold{25}, 400--405. Genz, A. and Bretz, F. (2002), Methods for the computation of multivariate t-probabilities. \emph{Journal of Computational and Graphical Statistics}, \bold{11}, 950--971. Genz, A. (2004), Numerical computation of rectangular bivariate and trivariate normal and t-probabilities, \emph{Statistics and Computing}, \bold{14}, 251--260. Genz, A. and Bretz, F. (2009), \emph{Computation of Multivariate Normal and t Probabilities}. Lecture Notes in Statistics, Vol. 195. Springer-Verlag, Heidelberg. Miwa, A., Hayter J. and Kuriki, S. (2003). The evaluation of general non-centred orthant probabilities. \emph{Journal of the Royal Statistical Society}, Ser. B, 65, 223--234. } \keyword{distribution}