Sufficient burn-in for Gibbs samplers for a hierarchical random effects model
| dc.creator | Jones, Galin L. | |
| dc.creator | Hobert, James P. | |
| dc.date | 2004-06-23 | |
| dc.date.accessioned | 2026-07-07T08:06:20Z | |
| dc.date.available | 2026-07-07T08:06:20Z | |
| dc.description | We consider Gibbs and block Gibbs samplers for a Bayesian hierarchical version of the one-way random effects model. Drift and minorization conditions are established for the underlying Markov chains. The drift and minorization are used in conjunction with results from J. S. Rosenthal [J. Amer. Statist. Assoc. 90 (1995) 558-566] and G. O. Roberts and R. L. Tweedie [Stochastic Process. Appl. 80 (1999) 211-229] to construct analytical upper bounds on the distance to stationarity. These lead to upper bounds on the amount of burn-in that is required to get the chain within a prespecified (total variation) distance of the stationary distribution. The results are illustrated with a numerical example. | |
| dc.identifier | https://arxiv.org/abs/math/0406454 | |
| dc.identifier | http://arxiv.org/abs/math/0406454 | |
| dc.identifier | Annals of Statistics 2004, Vol. 32, No. 2, 784-817 | |
| dc.identifier | doi:10.1214/009053604000000184 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/130570 | |
| dc.subject | Statistics Theory | |
| dc.subject | 60J10 (Primary) 62F15 (Secondary) | |
| dc.title | Sufficient burn-in for Gibbs samplers for a hierarchical random effects model | |
| dc.type | text |