An automatic method for generating random variates with a given characteristic function
SIAM Journal on Applied Mathematics
Multivariate statistical simulation
Multivariate statistical simulation
Efficient and portable combined random number generators
Communications of the ACM
SIAM Journal on Scientific and Statistical Computing
Hit-and-run algorithms for generating multivariate distributions
Mathematics of Operations Research
Algorithm 599: sampling from Gamma and Poisson distributions
ACM Transactions on Mathematical Software (TOMS)
Gamma variate generators with increased shape parameter range
Communications of the ACM
A rejection technique for sampling from log-concave multivariate distributions
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Algorithm 802: an automatic generator for bivariate log-concave distributions
ACM Transactions on Mathematical Software (TOMS)
A probabilistic framework for problems with real structured uncertainty in systems and control
Automatica (Journal of IFAC)
Univariate Bayesian nonparametric mixture modeling with unimodal kernels
Statistics and Computing
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A probability density on a finite-dimensional Euclidean space is orthounimodal with a given mode if within each orthant (quadrant) defined by the mode, the density is a monotone function of each of its arguments individually. Up to a linear transformation, most of the commonly used random vectors possess orthounimodal densities. To generate a random vector from a given orthounimodal density, several general-purpose algorithms are presented; and an experimental performance evaluation illustrates the potential efficiency increases that can be achieved by these algorithms versus naive rejection.