Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/188081 
Year of Publication: 
2013
Citation: 
[Journal:] Pakistan Journal of Commerce and Social Sciences (PJCSS) [ISSN:] 2309-8619 [Volume:] 7 [Issue:] 1 [Publisher:] Johar Education Society, Pakistan (JESPK) [Place:] Lahore [Year:] 2013 [Pages:] 157-165
Publisher: 
Johar Education Society, Pakistan (JESPK), Lahore
Abstract: 
In this paper, we present the computational procedure of the First-Order Model in Response Surface Methodology (RSM) in a new dimension. Firstly, we fit the First-Order Model to a 2k design by applying Yates' technique to calculate the sum of squares of main effects and their interactions. Secondly, we prove that SS regression and SS linear are equivalent. Thirdly, we give a new idea for computing SS quadratic under the concept of unbalanced Completely Randomized Design. The formula used in this technique is numerically and mathematically equivalent to the existing technique. Lastly, we split the total variation in the responses into all possible sources with the help of a diagram.
Subjects: 
Quadratic effect in response surface
first-order model
SS regression
SS linear
Creative Commons License: 
cc-by-nc Logo
Document Type: 
Article

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.