Fitting Second-order Models to Mixed Two-level and Four-level Factorial Designs: Is There an Easier Procedure?

Authors

  • Abbas Alkarkhi Faculty of technical foundation, Universiti kuala lumpur (Unikl)-Micet
Abstract:

Fitting response surface models is usually carried out using statistical packages to solve complicated equations in order to produce the estimates of the model coefficients. This paper proposes a new procedure for fitting response surface models to mixed two-level and four-level factorial designs. New and easier formulae are suggested to calculate the linear, quadratic and the interaction coefficients for mixed two-level and four-level factorial designs regardless of the number of factors included in the experiment. The results of the proposed procedure are in agreement with the results of least squares method. This paper could motivate researchers to study the possibility of applying a fixed formula to all factorial designs.

Download for Free

Sign up for free to access the full text

Already have an account?login

similar resources

Saturated Second-Order Two-Level Designs: An Empirical Approach

Computer methods are used to explore saturated designs which provide for optimal estimation of main e ects and interactions between two-level factors. A series of designs is thus discovered, related to a known series but better for k > 6. Also, a relationship is discovered between two di erent classes designs which should be fruitful for future research.

full text

Bayesian-inspired mixed two- and four-level designs

Motivated by a Bayesian framework, we propose a new minimum aberration type criterion for designing experiments with twoand four-level factors. The Bayesian approach helps in overcoming the ad hoc nature of effect ordering in the existing minimum aberration type criteria. Moreover, the approach is also capable of distinguishing between qualitative and quantitative factors. Numerous examples are...

full text

Optimal Foldover Plans for Two-Level Fractional Factorial Designs

A commonly used follow-up experiment strategy involves the use of a foldover design by reversing the signs of one or more columns of the initial design. DeŽ ning a foldover plan as the collection of columns whose signs are to be reversed in the foldover design, this article answers the following question: Given a 2kp design with k factors and p generators, what is its optimal foldover plan? We ...

full text

Optimal Designs for Two-level Factorial Experiments with Binary Response

We consider the problem of obtaining locally D-optimal designs for factorial experiments with qualitative factors at two levels each with binary response. Our focus is primarily on the 2 experiment. In this paper, we derive analytic results for some special cases and indicate how to handle the general case. The performance of the uniform design in examined and we show that this design is highly...

full text

Bayesian - inspired minimum aberration two - and four - level designs

Motivated by a Bayesian framework, we propose a new minimum aberration-type criterion for designing experiments with twoand four-level factors. The Bayesian approach helps in overcoming the ad hoc nature of effect ordering in the existing minimum aberration-type criteria. The approach is also capable of distinguishing between qualitative and quantitative factors. Numerous examples are given to ...

full text

My Resources

Save resource for easier access later

Save to my library Already added to my library

{@ msg_add @}


Journal title

volume 28  issue 11

pages  1644- 1650

publication date 2015-11-01

By following a journal you will be notified via email when a new issue of this journal is published.

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023