Efficient computational algorithm for optimal allocation in regression models

In this article, we discuss the optimal allocation problem in an experiment when a regression model is used for statistical analysis. Monotonic convergence for a general class of multiplicative algorithms for D-optimality has been discussed in the literature. Here, we provide an alternate proof of the monotonic convergence for D-criterion with a simple computational algorithm and furthermore show it converges to the D-optimality. We also discuss an algorithm as well as a conjecture of the monotonic convergence for A-criterion. Monte Carlo simulations are used to demonstrate the reliability, efficiency and usefulness of the proposed algorithms.