# Simulation of truncated normal variables

@article{Robert1995SimulationOT, title={Simulation of truncated normal variables}, author={Christian P. Robert}, journal={Statistics and Computing}, year={1995}, volume={5}, pages={121-125} }

We provide simulation algorithms for one-sided and two-sided truncated normal distributions. These algorithms are then used to simulate multivariate normal variables with convex restricted parameter space for any covariance structure.

## 509 Citations

### A completion simulator for the two-sided truncated normal distribution

- MathematicsGenetics Selection Evolution
- 2000

Simulation formulae of two-sided truncated normal random variables using a completion distribution and its two corresponding conditionals generated via a Gibbs sampler are presented.

### A Note on the Sum of Non-Identically Distributed Doubly Truncated Normal Distributions

- Mathematics
- 2020

It is proved that the sum of n independent but non-identically distributed doubly truncated Normal distributions converges in distribution to a Normal distribution. It is also shown how the result…

### Estimating Linear Mixed Effects Models with Truncated Normally Distributed Random Effects

- Mathematics
- 2020

It is proved that the sum of n independent but non-identically distributed doubly truncated Normal distributions converges in distribution to a Normal distribution. It is also shown how the result…

### Sampling Some Truncated Distributions Via Rejection Algorithms

- MathematicsCommun. Stat. Simul. Comput.
- 2010

Rejection sampling algorithms to sample from some truncated and tail distributions, including multivariate normal distributions truncated to certain sets, are developed.

### Fast Simulation of Hyperplane-Truncated Multivariate Normal Distributions

- Mathematics
- 2016

We introduce a fast and easy-to-implement simulation algorithm for a multivariate normal distribution truncated on the intersection of a set of hyperplanes, and further generalize it to efficiently…

### Simulation from the Tail of the Univariate and Multivariate Normal Distribution

- MathematicsSystems Modeling: Methodologies and Tools
- 2019

We study and compare various methods to generate a random variate or vector from the univariate or multivariate normal distribution truncated to some finite or semi-infinite region, with special…

### Perfect simulation of positive Gaussian distributions

- Computer ScienceStat. Comput.
- 2003

An exact simulation algorithm that produces variables from truncated Gaussian distributions on R via a perfect sampling scheme, based on stochastic ordering and slice sampling, since accept-reject algorithms like the one of Geweke and Robert are difficult to extend to higher dimensions.

### Sampling Normal Distribution Restricted on Multiple Regions

- MathematicsICONIP
- 2012

We develop an accept-reject sampler for probability densities that have the similar form of a normal density function, but supported on restricted regions. Compared to existing techniques, the…

### Maximum Likelihood Variance Components Estimation for Binary Data

- Mathematics
- 1994

Abstract We consider a class of probit-normal models for binary data and describe ML and REML estimation of variance components for that class as well as best prediction for the realized values of…

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