A Simulation Study of the Performance of Five Discriminant Analysis Methods for Mixtures of Continuous and Binary Variables
DOI10.1080/00949658508810859zbMath0593.62059OpenAlexW2120321700MaRDI QIDQ3723508
No author found.
Publication date: 1985
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00949658508810859
location modelcontinuous variablesmethodsbinary variablesindependence modelquadratic discriminationlogistic discriminationFisher's linear discriminationkernel modelmixtures of variablessimulation study of the performance of discriminant analysis
Classification and discrimination; cluster analysis (statistical aspects) (62H30) Probabilistic methods, stochastic differential equations (65C99)
Cites Work
- Decision rule, based on the distance, for the classification problem
- Distance between populations using mixed continuous and categorical variables
- Mixtures of Continuous and Categorical Variables in Discriminant Analysis
- A simulative comparison of linear, quadratic and kernel discrimination
- Comparison of Discrimination Techniques Applied to a Complex Data Set of Head Injured Patients
- Separate sample logistic discrimination
- Unnamed Item
- Unnamed Item
- Unnamed Item
This page was built for publication: A Simulation Study of the Performance of Five Discriminant Analysis Methods for Mixtures of Continuous and Binary Variables
