Monotonic convergence of a general algorithm for computing optimal designs
Open Access
- 1 June 2010
- journal article
- Published by Institute of Mathematical Statistics in The Annals of Statistics
- Vol. 38 (3)
- https://doi.org/10.1214/09-aos761
Abstract
Monotonic convergence is established for a general class of multiplicative algorithms introduced by Silvey, Titterington and Torsney [Comm. Statist. Theory Methods 14 (1978) 1379--1389] for computing optimal designs. A conjecture of Titterington [Appl. Stat. 27 (1978) 227--234] is confirmed as a consequence. Optimal designs for logistic regression are used as an illustration.Comment: Published in at http://dx.doi.org/10.1214/09-AOS761 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.orgKeywords
All Related Versions
This publication has 23 references indexed in Scilit:
- D-optimal designs for logistic models with three and four parametersJournal of Statistical Planning and Inference, 2008
- Bayesian Experimental Design: A ReviewStatistical Science, 1995
- Optimal Weights for Experimental Designs on Linearly Independent Support PointsThe Annals of Statistics, 1991
- Optimal Bayesian design applied to logistic regression experimentsJournal of Statistical Planning and Inference, 1989
- The Convergence of General Step-Length Algorithms for Regular Optimum Design CriteriaThe Annals of Statistics, 1978
- Estimation of Correlation Coefficients by Ellipsoidal TrimmingJournal of the Royal Statistical Society Series C: Applied Statistics, 1978
- General Equivalence Theory for Optimum Designs (Approximate Theory)The Annals of Statistics, 1974
- Sequences Converging to $D$-Optimal Designs of ExperimentsThe Annals of Statistics, 1973
- The Equivalence of Two Extremum ProblemsCanadian Journal of Mathematics, 1960
- Locally Optimal Designs for Estimating ParametersThe Annals of Mathematical Statistics, 1953