Khizar Hayat Khan
Department of Mathematics, College of Science and Humanities, Prince Sattam Bin Abdulaziz University, Al-Kharj, Kingdom of Saudi Arabia
*Corresponding author: Khizar Hayat Khan
Email: drkhizar@gmail.com, k.khan@psau.edu.sa
Abstract
We find Survival rate estimates; parameter estimates for the
inverse Gaussian distribution model using least-squares estimation method. We
found these estimates for the case when partial derivatives were available and
for the case when partial derivatives were not available. The simplex
optimization (Nelder and Mead, and Hooke and Jeeves) methods were used for the
case when first partial derivatives were not available and the Quasi – Newton
optimization (Davidon-Fletcher-Powel (DFP) and the
Broyden-Fletcher-Goldfarb-Shanno (BFGS) methods were applied for the case when
first partial derivatives were available. The medical data sets of 21 Leukemia
cancer patients with time span of 35 weeks were used.
How to cite this paper
Parameter Estimation with Least-Squares Method for the Inverse Gaussian distribution Model Using Simplex and Quasi-Newton Optimization Methods
How to cite this paper: Khan, K. H. (2018) Parameter Estimation with Least-Squares Method for the Inverse Gaussian distribution Model Using Simplex and Quasi-Newton Optimization Methods. Journal of Applied Mathematics and Computation, 2(10), 466-472.
DOI: 10.26855/jamc.2018.10.002
