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process-improve 1.13.11 documentation

  • Quick Start
  • User Guide
  • API Reference
  • GitHub
  • Quick Start
  • User Guide
  • API Reference
  • GitHub

Section Navigation

  • Multivariate Analysis
    • Principal Component Analysis (PCA)
    • Projection to Latent Structures (PLS)
    • T-shaped Partial Least Squares (TPLS)
    • Multi-block PCA and PLS (MBPCA / MBPLS)
  • Selecting the Number of Components
  • Experimental Strategy Recommendation
  • Case studies
    • Latent variable modelling
      • PCA on NIR tablet spectra
      • PCA on food texture
      • PCA with missing data: Kamyr digester
    • Least squares modelling
      • Regressing cheddar taste on chemical composition
    • Design and analysis of experiments
      • Factorial DOE: oil-company experiment
    • Process monitoring
      • Control charts for rubber colour
  • User Guide
  • Case studies
  • Latent variable modelling

Latent variable modelling#

Worked case studies that use principal component analysis (PCA) and projection to latent structures (PLS) on real process and product data.

  • PCA on NIR tablet spectra
  • PCA on food texture
  • PCA with missing data: Kamyr digester

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Case studies

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PCA on NIR tablet spectra

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