Abstract
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.
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References
Chen, M. H. and Deely, J. (1992) Application of a new Gibbs Hit-and-Run sampler to a constrained linear multiple regression problem. Technical report, Purdue University, Lafayette, IN.
Devroye, L. (1985) Non-uniform random variate generation. Springer-Verlag, New York.
Dykstra, R. L. and Robertson, T. (1982) An algorithm for isotonic regression for two or more independent variables. Annals of Statistics, 10, 708–716.
Gelfand, A. E. and Smith, A. F. M. (1990) Sampling based approaches to calculating marginal densities. Journal of the American Statistical Association, 85, 398–409.
Gelfand, A. E., Smith, A. F. M. and Lee, T. M. (1992) Bayesian analysis of constrained parameter and truncated data problems using Gibbs sampling. Journal of the American Statistical Association, 87, 523–532.
Gelman, A. and Rubin, D. B. (1992) Inference from iterative simulation using multiple sequences (with discussion). Statistical Science, 7, 457–511.
Geyer, C. J. (1992) Practical Monte-Carlo Markov Chain (with discussion). Statistical Science, 7, 473–511.
Hastings, W. K. (1971) Monte-Carlo sampling methods using Markov chains and their applications. Biometrika, 57, 97–109.
Marsaglia, G. (1964) Generating a variable from the tail of a normal distribution. Technometrics, 6, 101–102.
Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H. and Teller, E. (1953) Equations of state calculations by fast computing machines. Journal of Chemical Physics, 21, 1087–91.
Qian, W. and Titterington, D. M. (1991) Estimation of parameters in hidden Markov models. Philosophical Transactions of the Royal Society of London A, 337, 407–428.
Ripley, B. D. (1987) Stochastic simulation. Wiley, New York.
Robertson, T., Wright, F. T. and Dykstra, R. L. (1988) Order restricted statistical inference. Wiley, New York.
Tanner, M. (1993) Tools for statistical inference, 2nd edn. Springer-Verlag, New York.
Tanner, M. and Wong, W. (1987) The calculation of posterior distributions by data augmentation. Journal of the American Statistical Association, 82, 528–550.
Tierney, L. (1991) Markov chains for exploring posterior distributions. Computer Sciences and Statistics: Proceedings of the 23 Symposium on the Interface, 563–570.
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Robert, C.P. Simulation of truncated normal variables. Stat Comput 5, 121–125 (1995). https://doi.org/10.1007/BF00143942
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DOI: https://doi.org/10.1007/BF00143942