Date of Graduation
8-1986
Document Type
Dissertation
Degree Name
Doctor of Philosophy in Business Administration (PhD)
Degree Level
Graduate
Department
Accounting
Advisor/Mentor
Jones, Thomas W.
Committee Member
Douglas, David E.
Second Committee Member
Williams, Nolan E.
Keywords
Linear programming model; quadratic programming model; Monte Carlo techniques
Abstract
The purpose of this research was to compare the classification accuracy of two mathematical programming models versus traditional statistical discriminant analysis. Monte Carlo techniques were used to compute population 1, population 2, and average misclassification rates for the linear discriminant function (LDF), the quadratic discriminant function (QDF), a linear programming discriminant model (LPDM), and a quadratic programming discriminant model (QPDM) for specific values of several parameters which affect discriminant analysis. This study was restricted to the two group, two variable discriminant problem.
Citation
Ferry, J. W. (1986). A Comparison of the Classification Accuracy of Linear and Quadratic Statistical Discriminant Models versus Linear and Quadratic Programming Discriminant Models. Graduate Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/3438
Included in
Accounting Commons, Business Administration, Management, and Operations Commons, Finance and Financial Management Commons
