Abstract
Abstract We use the criterion of D-optimality of the Fisher information matrix to derive optimal vectors for binary data. Some concepts of totally positive functions and Polya functions of order II are used to derive properties of the determinant of the Fisher information matrix arising in quantal response bioassay and attribute life testing models. As is often the case in non-linear models the D-optimal vectors are functions of the unknown parameters. By using the criterion of D-optimality, general optimal vectors are characterized which could be used for constructing Bayesian or locally D-optimal designs.
Full Text 
Sign-in/Register to access full text options
Sign-in/Register to access full text options 
Paper version not known
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
