Variable and model selection problems are fundamental to high-dimensional statistical modeling in diverse fields of sciences. Especially in health studies, many potential factors are usually introduced to determine an outcome variable. This paper deals with the problem of high-dimensional...

Hadamard matrices have traditionally been used for screening main effects only, because of their complex aliasing structures. The hidden projection property, as introduced by Wang and Wu (Statistica Sinica 5 (1995) 235-250), suggests that complex aliasing allows some interactions to be...

Screening designs are useful for situations where a large number of factors (q) is examined but only few (k) of these are expected to be important. [Plackett and Burman 1946] designs and Hadamard matrices have traditionally been studied for this purpose. (Box, G.E.P., Tyssedal, J., 1996....

Suppose a large number of two-level factors is examined in an experimental situation. Under the assumption of effect sparsity it is often anticipated that only a few experimental factors play an important role in the experiment. Usually, it is not known which columns of the experimental design...

Suppose it is desired to have an optimal resolution III fraction of a 2p factorial in n runs where n[reverse not equivalent]1 (mod 4) or n[reverse not equivalent]3 (mod 4). If n[reverse not equivalent]1 (mod 4), we have to decide if we should add a run in a nxp submatrix of a Hadamard matrix of...