Supersaturated designs (SSDs) can save considerable cost in industrial experimentation when many potential factors are introduced in preliminary studies. Analyzing data in SSDs is challenging because the number of experiments is less than the number of candidate factors. In this paper, we...

When experimentation is expensive and the number of factors is large, supersaturated designs can be helpful. They are essentially fractional factorial designs in which the number of factors is greater than the number of experimental runs. Previous studies have focused on two-level supersaturated...

Orthogonality has been considered as an important design priority in the design literature. This article provides a set of criteria to measure "how orthogonal" a design may be when it is not perfectly orthogonal. These criteria can be obviously applied to a wide variety of designs. Properties of...

The Kalman filter, which is in popular use in various branches of engineering, is essentially a least squares procedure. One well-recognized concern in this least squares procedure is its non-robustness to spuriously generated observations that give rise to outlying observations, rendering the...

This note provides a theoretical justification for the optimal foldover plans for two-level designs, including the regular 2s-p, non-regular, saturated and supersaturated designs.

We explore the impact of dispersion effects on location effect estimation and derive approximate joint confidence regions for pairs of correlated location effect estimates. A procedure for estimating location effects in the presence of a single dispersion effect is recommended.

The Kalman filter is probably the most popular recursive estimation method. It is, however, known to be non-robust to spuriously generated observations. Much attention has been focused on finding the so-called robust recursive estimation under the assumption that the observations are...