Citation map · Study

SZodixStudyAcademic Library

Shelves Open access

Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated

LASSO-based diagnosis scheme for multistage processes with binary data

16 references·3 citing·35 second hop

FromToDepth

this work references cited by second hop

References

2002Multivariate Statistical Process Control with Industrial Applications443 cited
1995Decomposition of T 2 for Multivariate Control Chart Interpretation397 cited
1991Multivariate Quality Control Based on Regression-Adjusted Variables378 cited
1985Multivariate quality control296 cited
1997A Practical Approach for Interpreting Multivariate T2 Control Chart Signals252 cited
2009Multivariate Statistical Process Control Using LASSO225 cited
1994Identification and Quantification in Multivariate Quality Control Problems140 cited
1991Identification of out of control quality characteristics in a multivariate manufacturing environment132 cited
2012A Variable-Selection-Based Multivariate EWMA Chart for Process Monitoring and Diagnosis85 cited
2000Change-point detection of mean vector or covariance matrix shifts using multivariate individual observations78 cited
2008Directional MEWMA Schemes for Multistage Process Monitoring and Diagnosis77 cited
2001Applying Hotelling'sT2 Statistic to Batch Processes77 cited
2009False Discovery Rate-Adjusted Charting Schemes for Multistage Process Monitoring and Fault Identification76 cited
2004Artificial neural networks to classify mean shifts from multivariate χ2 chart signals72 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

2002

Detection of Multiple Change Points from Clustering Individual Observations

64 cited

2012Monitoring the covariance matrix via penalized likelihood estimation59 cited

Cited by

2015Statistical monitoring of over-dispersed multivariate count data using approximate likelihood ratio tests12 cited
2017Detecting entropy increase in categorical data using maximum entropy distribution approximations12 cited
2018Phase I outlier detection in profiles with binary data based on penalized likelihood12 cited