ALL POSSIBLE HIERARCHICAL QUADRATIC REGRESSIONS FOR RESPONSE SURFACES

In response surfaces analysis, we often proceed by supposing that, over a limited region of factor space, a polynomial of only first or second degree might adequately approximate the true function. To find the best subset model, all possible quadratic regressions for response surfaces can be very valuable to get optimum solutions under some reasonable experimentations. However, there is a very hard computational burden to get all possible quadratic regressions. In practice, it is sufficient to consider only hierarchical models. In this paper, we propose an algorithm to get all possible hierarchical quadratic regressions for fitting response surfaces.