Maximum Likelihood estimation under two-stage adaptive designs with finite first-stage samples

In this work, we study the properties of the maximum likelihood estimator (MLE) for the vector parameter of a non-linear model with Gaussian errors. To estimate the multidimensional parameter as precisely as possible, the experimental conditions are chosen according to a two-stage design. The observations[for full text, please go to the a.m. URL]
65th Annual Meeting of the German Association for Medical Informatics, Biometry and Epidemiology (GMDS), Meeting of the Central European Network (CEN: German Region, Austro-Swiss Region and Polish Region) of the International Biometric Society (IBS)