In practice, optimal screening designs for arbitrary run sizes are traditionally generated using the D-criterion with factor settings fixed at ±1, even when considering continuous factors levels in [−1,1]. This article identifies cases of undesirable estimation variance properties such D-optimal and argues that generally A-optimal tend to push variances closer their minimum possible value. New ...

In life-testing experiments, it is often of interest to predict unobserved future failure times based on observed early times. A point best linear unbiased predictor (BLUP) has been developed in this context by Kaminsky and Nelson (J Am Stat Assoc 70:145–150, 1975). article, we develop joint BLUPs two minimizing the determinant variance–covariance matrix predictors. The advantage applying predi...

Mitscherlich’s function is a well-known three-parameter non-linear regression that quantifies the relation between stimulus or time variable and response. It has many applications, in particular field of measurement reliability. Optimal designs for estimation this have been constructed only normally distributed responses with homoscedastic variances. In paper we generalize literature to D-optim...