Optimal experimental designs are probability measures with finite support enjoying an optimality property for the computation of least squares estimators. We present an algorithm for computing optimal designs on finite sets based on the long-time asymptotics of the gradient flow of the log-determinant of the so called information matrix. We prove the convergence of the proposed algorithm, and provide a sharp estimate on the rate its convergence. Numerical experiments are performed on few test cases using the new matlab package OptimalDesignComputation.

翻译：最佳实验设计是概率度量,有有限的支持,在计算最小正方位估测器时享有最佳性能。我们根据所谓的信息矩阵的日志确定性梯度流的长期停滞状态,提出计算有限组装最佳设计的最佳性能算法。我们证明了拟议的算法的趋同性,并提供了其趋同率的粗略估计。使用新毛板包件“最佳设计”对少数试验案例进行了数字性实验。