Open AccessBayesian Sensitivity-Specificity and ROC Analysis for Finding Key Drivers
Author(s) -
Stan Lipovetsky,
Michael Conklin
Publication year - 2021
Publication title -
journal of modern applied statistical methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.169
H-Index - 28
ISSN - 1538-9472
DOI - 10.22237/jmasm/1619481960
Subject(s) - key (lock) , sensitivity (control systems) , bayesian probability , receiver operating characteristic , statistics , machine learning , regression analysis , bayesian linear regression , mathematics , regression , artificial intelligence , econometrics , computer science , data mining , bayesian inference , engineering , computer security , electronic engineering
Finding key drivers in regression modeling via Bayesian Sensitivity-Specificity and Receiver Operating Characteristic is suggested, and clearly interpretable results are obtained. Numerical comparisons with other techniques show that this methodology can be useful in practical statistical modeling and analysis helping to researchers and managers in making meaningful decisions.