Popular decision rules in SIMCA: Critical review

[1]  Theodora Kourti,et al.  Statistical Process Control of Multivariate Processes , 1994 .

[2]  Erik Johansson,et al.  Four levels of pattern recognition , 1978 .

[3]  Paul Geladi,et al.  Principal Component Analysis , 1987, Comprehensive Chemometrics.

[4]  G. Box Some Theorems on Quadratic Forms Applied in the Study of Analysis of Variance Problems, I. Effect of Inequality of Variance in the One-Way Classification , 1954 .

[5]  Oxana Ye. Rodionova,et al.  Path modeling and process control , 2007 .

[6]  A. Pomerantsev,et al.  Detection of outliers in projection based modeling. , 2019, Analytical chemistry.

[7]  Satterthwaite Fe An approximate distribution of estimates of variance components. , 1946 .

[8]  Agnar Höskuldsson,et al.  Process control and optimization with simple interval calculation method , 2006 .

[9]  Barry M. Wise,et al.  The process chemometrics approach to process monitoring and fault detection , 1995 .

[10]  Welch Bl THE GENERALIZATION OF ‘STUDENT'S’ PROBLEM WHEN SEVERAL DIFFERENT POPULATION VARLANCES ARE INVOLVED , 1947 .

[11]  S. Joe Qin,et al.  Statistical process monitoring: basics and beyond , 2003 .

[12]  S. Wold,et al.  SIMCA: A Method for Analyzing Chemical Data in Terms of Similarity and Analogy , 1977 .

[13]  A. Pomerantsev,et al.  Concept and role of extreme objects in PCA/SIMCA , 2014 .

[14]  J. E. Jackson,et al.  Control Procedures for Residuals Associated With Principal Component Analysis , 1979 .

[15]  Károly Héberger,et al.  Is soft independent modeling of class analogies a reasonable choice for supervised pattern recognition , 2018 .

[16]  Alexey L. Pomerantsev,et al.  Confocal Raman spectroscopy and multivariate data analysis for evaluation of spermatozoa with normal and abnormal morphology. A feasibility study , 2018, Chemometrics and Intelligent Laboratory Systems.

[17]  P. Oliveri Class-modelling in food analytical chemistry: Development, sampling, optimisation and validation issues - A tutorial. , 2017, Analytica chimica acta.

[18]  Olav M. Kvalheim,et al.  A method for validation of reference sets in SIMCA modelling , 2004 .

[19]  Oxana Ye. Rodionova,et al.  Rigorous and compliant approaches to one-class classification , 2016 .

[20]  S H Scafi,et al.  Identification of counterfeit drugs using near-infrared spectroscopy. , 2001, The Analyst.

[21]  A. Pomerantsev Acceptance areas for multivariate classification derived by projection methods , 2008 .

[22]  Alberto Ferrer,et al.  Multivariate Statistical Process Control Based on Principal Component Analysis (MSPC-PCA): Some Reflections and a Case Study in an Autobody Assembly Process , 2007 .

[23]  Ali Cinar,et al.  Statistical process monitoring and disturbance diagnosis in multivariable continuous processes , 1996 .

[24]  A L Pomerantsev,et al.  Detection of counterfeit and substandard tablets using non-invasive NIR and chemometrics - A conceptual framework for a big screening system. , 2019, Talanta.

[25]  Oxana Ye. Rodionova,et al.  On the type II error in SIMCA method , 2014 .

[26]  M. Hubert,et al.  Robust classification in high dimensions based on the SIMCA Method , 2005 .