9 citations · 14 across the 6 of their papers we have counts for
6 papers
Minimax Robust Designs for M-Estimated Models
Rui Hu, Douglas P. Wiens
Experimental designs that are minimax in the presence of model misspecifications have been constructed so as to minimize the maximum, over classes of alternate response models, of…
Minimum Variance Designs With Constrained Maximum Bias
Douglas P. Wiens
Designs which are minimax in the presence of model misspecifications have been constructed so as to minimize the maximum, over classes of alternate response models, of the integrat…
To ignore dependencies is perhaps not a sin
Douglas P. Wiens
We present a result according to which certain functions of covariance matrices are maximized at scalar multiples of the identity matrix. In a statistical context in which such fun…
A Note on Minimax Robustness of Designs Against Correlated or Heteroscedastic Responses
Douglas P. Wiens
We present a result according to which certain functions of covariance matrices are maximized at scalar multiples of the identity matrix. This is used to show that experimental des…
Jittering and Clustering: Strategies for the Construction of Robust Designs
Douglas Wiens
We discuss, and give examples of, methods for randomly implementing some minimax robust designs from the literature. These have the advantage, over their deterministic counterparts…
Model-Robust Designs for Quantile Regression
Linglong Kong, Douglas P. Wiens
We give methods for the construction of designs for linear models, when the purpose of the investigation is the estimation of the conditional quantile function and the estimation m…