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. Yu (Monotonic Convergence of a general algorithm for computing optimal designs. Annual of Statistics, 38, 2010: 1593-1606) has established the monotonic convergence for a general class of multiplicative algorithms for D-optimality. Here, we provide an alternate proof of the monotonic convergence for D-criterion with a simple computational algorithm. 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.