Year of Publication
College of Arts and Sciences
Master of Science in Mathematical Sciences (MS)
Mathematics & Statistics
Dr. Donna Mohr
Dr. Peter Wludyka
Dr. Ping Sa
Confidence Bands for Nonlinear Regression Functions can be found analytically for a very limited range of functions with a restrictive parameter space. A computer intensive technique, the Monte Carlo Method will be used to develop an algorithm to find confidence bands for any given nonlinear regression functions with a broader parameter space.
The logistic regression function with one independent variable and two parameters will be used to test the validity and efficiency of the algorithm. The confidence bands for this particular function have been solved for analytically by Khorasani and Milliken (1982). Their derivations will be used to test the Monte Carlo algorithm.
Mazumdar, Shantonu, "Monte Carlo Methods for Confidence Bands in Nonlinear Regression" (1995). UNF Theses and Dissertations. 185.