We consider a class of optimality criteria and show that each crite- rion has its unique and equivalent dual within the class. This property can be used to find a variety of optimal designs, including a class of compound optimal designs and their relationships. As an example, we show that one...

We consider a class of optimality criteria and show that each crite- rion has its unique and equivalent dual within the class. This property can be used to find a variety of optimal designs, including a class of compound optimal designs and their relationships. As an example, we show that one...

Logistic regressions are commonly used to assess for fair lending across groups of loan applicants. This paper considers estimation of the disparate treatment parameter when the sample is stratified jointly by loan outcome and race covariate. We use Monte Carlo analysis to investigate the...

In this paper the problem of designing experiments for a model which is called Monod model and is frequently used in microbiology is studied. The model is defined implicitly by a differential equation and has numerous applications in microbial growth kinetics, environmental research,...

In this paper D-optimal designs for free knot least squares spline estimation are investigated. In contrast to most of the literature on optimal design for spline regression models it is assumed that the knots of the spline are also estimated from the data, which yields to optimal design...

We discuss optimal design problems for a popular method of series estimation in regression problems. Commonly used design criteria are based on the generalized variance of the estimates of the coefficients in a truncated series expansion and do not take possible bias into account. We present a...

If a model is fitted to empirical data, bias can arise from terms which are not incorporated in the model assumptions. As a consequence the commonly used optimality criteria based on the generalized variance of the estimate of the model parameters may not lead to efficient designs for the...