Residual Control Chart for Binary Response with Multicollinearity Covariates by Neural Network Model
Document Type
Article
Publication Date
2020
DOI
10.3390/sym12030381
Publication Title
Symmetry
Volume
12
Issue
3
Pages
381 (1-15)
Abstract
Quality control studies have dealt with symmetrical data having the same shape with respect to left and right. In this research, we propose the residual (r) control chart for binary asymmetrical (non-symmetric) data with multicollinearity between input variables via combining principal component analysis (PCA), functional PCA (FPCA) and the generalized linear model with probit and logit link functions, and neural network regression model. The motivation in this research is that the proposed control chart method can deal with both high-dimensional correlated multivariate data and high frequency functional multivariate data by neural network model and FPCA. We show that the neural network r control chart is relatively efficient to monitor the simulated and real binary response data with the narrow length of control limits.
Original Publication Citation
Kim, J. M., Wang, N., Liu, Y., & Park, K. (2020). Residual control chart for binary response with multicollinearity covariates by neural network model. Symmetry, 12(3), 381. doi:10.3390/sym12030381
Repository Citation
Kim, Jong-Min; Wang, Ning; Liu, Yumin; and Park, Kayoung, "Residual Control Chart for Binary Response with Multicollinearity Covariates by Neural Network Model" (2020). Mathematics & Statistics Faculty Publications. 169.
https://digitalcommons.odu.edu/mathstat_fac_pubs/169
Comments
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license.