Bootstrap Nonlinear Regression Application in a Design of an Experiment Data for Fewer Sample Size
Oyedele Adeshina Bello, Timothy Adebayo Bamiduro, Unna Angela Chuwkwu, Oyedeji Isola Osowole · arXiv (Cornell University) · 2015
This paper reports on application of bootstrap nonlinear regression method to a design of an experiment dataset with fewer experimental runs. Design with desired properties was augmented and verified using graphical techniques. The augmented design with the desired properties benefited the accuracy of the approximated function used. The computation power of R-language and SAS for computing nonlinear function and bootstrap was also compared.