Date of Award
8-2018
Degree Type
Thesis
Degree Name
Master of Science - Mathematical Sciences
Department
Mathematics and Statistics
First Advisor
Kent Riggs
Second Advisor
Robert K. Henderson
Third Advisor
Jacob Turner
Fourth Advisor
Garland Simmons
Abstract
This thesis is based on a Poisson model that uses both error-free data and error-prone data subject to misclassification in the form of false-negative and false-positive counts. We present maximum likelihood estimators (MLEs), Fisher's Information, and Wald statistics for Poisson rate parameter and the two misclassification parameters. Next, we invert the Wald statistics to get asymptotic confidence intervals for Poisson rate parameter and false-negative rate parameter. The coverage and width properties for various sample size and parameter configurations are studied via a simulation study. Finally, we apply the MLEs and confidence intervals to one real data set and another realistic data set.
Repository Citation
Poddiwala Hewage, Nishantha Janith Chandrasena, "Wald Confidence Intervals for a Single Poisson Parameter and Binomial Misclassification Parameter When the Data is Subject to Misclassification" (2018). Electronic Theses and Dissertations. 202.
https://scholarworks.sfasu.edu/etds/202
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Tell us how this article helped you.