Searching for D-Efficient Equivalent-Estimation Second-Order Split-Plot Designs

Searching for D-efficient Equivalent-Estimation Second-Order Split-Plot Designs

Several industrial experiments are set up using second-order splitplot designs (SPDs). These experiments have two types of factors: whole-plot (WP) factors and sub-plot (SP) factors. WP factors, also called hard-to-change factors are factors whose levels are hard or expensive to change. SP factors, also called easy-to-change factors are factors whose levels are easy or less expensive to change....

An Algorithm for Finding D-e cient Equivalent-Estimation Second-Order Split-Plot Designs

Many industrial experiments involve restricted rather than complete randomization. This often leads to the use of split-plot designs, which limit the number of independent settings of some of the experimental factors. These factors, named whole-plot factors, are often, in some way, hard to change. The remaining factors, called sub-plot factors, are easier to change. Their levels are therefore i...

Unbalanced and Minimal Point Equivalent Estimation Second-Order Split-Plot Designs

Restricting the randomization of hard-to-change factors in industrial experiments is often performed by employing a split-plot design structure. From an economic perspective, these designs minimize the experimental cost by reducing the number of resets of the hard-tochange factors. In this paper, unbalanced designs are considered for cases where the subplots are relatively expensive and the exp...

Cost-penalized estimation and prediction evaluation for split-plot designs

Split Plot and Strip Plot Designs

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