Chemometric Software supporting NSF Project Variable Selection for Remedying the Effects of Uncontrolled Variation in Data Driven Predictions
Loading...
Date
Journal Title
Journal ISSN
Volume Title
Publisher
Steven D. Brown
Abstract
Description
Software is provided as a deliverable product for NSF project Variable Selection for Remedying the Effects of Uncontrolled Variation in Data Driven Predictions (NSF Grant Number 1506853). There are 8 separate software packages, each provided in its own folder. Each folder includes a README file and example data to permit testing. The packages implement work published in the following papers:
D. Poerio and S.D. Brown, “Stacked Interval Sparse Partial Least Squares Regression Analysis,” Chemom. Intell. Lab Syst. 166, 2017, 49-60. (DOI: 10.1016/j.chemolab.2017.03.006)
D. Poerio and S.D. Brown, “Dual-Domain Calibration Transfer by Orthogonal Projection” , Appl. Spectrosc., 2018. (DOI: 10.1177/0003702817724164).Erratum to Dual-domain calibration transfer using orthogonal projection. Appl. Spectrosc. 2018, (DOI: 10.1177/0003702818768732)
D. Poerio and S.D. Brown, A Frequency-Localized Recursive Partial Least Squares Ensemble for Soft Sensing, J. Chemom. e2999, 2018. (DOI: 10.1002/cem.2999)
D. Poerio and S.D. Brown, “Highly-Overlapped, Recursive Partial Least Squares Soft Sensor with State Partitioning via Local Variable Selection”,Chemom. Intell. Lab Syst. 175 (2018) 104–115. (DOI: 10.1016/j.chemolab.2018.02.006)
C. Kneale and S.D. Brown, “Small Moving-Window Calibration Models for Soft Sensing Processes with Limited History.” Chemom. Intell. Lab. Syst.183, 2018, 36-46. (DOI: 10.1016/j.chemolab.2018.10.007)
C. Kneale and S.D. Brown, Band Target Entropy Minimization and Target Partial Least Squares for Spectral Recovery and Calibration, Analyt. Chim. Acta, 1031 (2018) 38-46. (DOI:10.1016/j.aca.2018.07.054)
D. Poerio and S.D. Brown, Localized and Adaptive Soft Sensor Based on an Extreme Learning Machine with Automated Self-correction Strategies, J. Chemom., 2018;e3088. (DOI: 10.1002/cem.3088)
C. Kneale and S.D. Brown, Exploratory Data Analysis using an Uncharted Forest, Talanta 189 (2018) 71–78. (DOI: 10.1016/j.talanta.2018.06.061)
D. Poerio and S.D. Brown, “Stacked Interval Sparse Partial Least Squares Regression Analysis,” Chemom. Intell. Lab Syst. 166, 2017, 49-60. (DOI: 10.1016/j.chemolab.2017.03.006)
D. Poerio and S.D. Brown, “Dual-Domain Calibration Transfer by Orthogonal Projection” , Appl. Spectrosc., 2018. (DOI: 10.1177/0003702817724164).Erratum to Dual-domain calibration transfer using orthogonal projection. Appl. Spectrosc. 2018, (DOI: 10.1177/0003702818768732)
D. Poerio and S.D. Brown, A Frequency-Localized Recursive Partial Least Squares Ensemble for Soft Sensing, J. Chemom. e2999, 2018. (DOI: 10.1002/cem.2999)
D. Poerio and S.D. Brown, “Highly-Overlapped, Recursive Partial Least Squares Soft Sensor with State Partitioning via Local Variable Selection”,Chemom. Intell. Lab Syst. 175 (2018) 104–115. (DOI: 10.1016/j.chemolab.2018.02.006)
C. Kneale and S.D. Brown, “Small Moving-Window Calibration Models for Soft Sensing Processes with Limited History.” Chemom. Intell. Lab. Syst.183, 2018, 36-46. (DOI: 10.1016/j.chemolab.2018.10.007)
C. Kneale and S.D. Brown, Band Target Entropy Minimization and Target Partial Least Squares for Spectral Recovery and Calibration, Analyt. Chim. Acta, 1031 (2018) 38-46. (DOI:10.1016/j.aca.2018.07.054)
D. Poerio and S.D. Brown, Localized and Adaptive Soft Sensor Based on an Extreme Learning Machine with Automated Self-correction Strategies, J. Chemom., 2018;e3088. (DOI: 10.1002/cem.3088)
C. Kneale and S.D. Brown, Exploratory Data Analysis using an Uncharted Forest, Talanta 189 (2018) 71–78. (DOI: 10.1016/j.talanta.2018.06.061)