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Title Author(s) Year Tags
Latent variable methods: Case studies in the food industry Nichols 2011
Latent variable multivariate regression modeling Burnham, MacGregor and Viveros-Aguilera 1999
Notes on the history and nature of partial least squares (PLS) modelling Geladi 1988
Product optimization and control in the latent variable space of nonlinear PLS models Yacoub and MacGregor 2004
Industrial batch data analysis using latent variable methods Rodrigues 2006
Data-based latent variable methods for process analysis, monitoring and control MacGregor, Yu, García-Muñoz and Flores-Cerrillo 2005
Mixture product design using latent variable methods Muteki 2006
Multivariate design Wold, Sjöström, Carlson, Lundstedt, Hellberg, Skagerberg, Wikström and Öhman 1986
Product design through multivariate statistical analysis of process data Jaeckle and MacGregor 1998
Quality control for batch processes using multivariate latent variable methods Flores-Cerrillo 2003
Product transfer between plants using historical process data Jaeckle and MacGregor 2000
Batch process modeling and MSPC Wold, Kettaneh-Wold, MacGregor and Dunn 2009
Interpretation of regression coefficients under a latent variable regression model Burnham, MacGregor and Viveros-Aguilera 2001
Development of inferential process models using PLS Kresta, Marlin and MacGregor 1994
Batch process improvement using latent variable methods García-Muñoz 2004
Frameworks for latent variable multivariate regression Burnham, Viveros-Aguilera and MacGregor 1996
Analysis, monitoring and fault diagnosis of batch processes using multiblock and multiway PLS Kourti, Nomikos and MacGregor 1995
Learning from data using latent variable methods Yacoub 2006
Review of adaptation mechanisms for data-driven soft sensors Kadlec, Grbić and Gabrys 2011
Analysis of multi-way (multi-mode) data Geladi 1989
Analysis of multiblock and hierarchical PCA and PLS models Westerhuis, Kourti and MacGregor 1998
Product and process improvement using latent variable methods Jaeckle 1998
Modified jack-knife estimation of parameter uncertainty in bilinear modelling by partial least squares regression (PLSR) Martens and Martens 2000
Mixture designs and models for the simultaneous selection of ingredients and their ratios Muteki, MacGregor and Ueda 2007
Using on-line process data to improve quality: challenges for statisticians MacGregor 1997
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