Publicaciones en colaboración con investigadores/as de Wageningen UR (11)

2024

  1. A Simulation Study of the Effects of Additive, Multiplicative, Correlated, and Uncorrelated Errors on Principal Component Analysis

    Journal of Chemometrics

2021

  1. All sparse PCA models are wrong, but some are useful. Part II: Limitations and problems of deflation

    Chemometrics and Intelligent Laboratory Systems, Vol. 208

2020

  1. 4.18 - Chemometrics Analysis of Big Data

    Comprehensive Chemometrics: Chemical and Biochemical Data Analysis, Second Edition: Four Volume Set (Elsevier), pp. 437-458

  2. All sparse PCA models are wrong, but some are useful. Part I: Computation of scores, residuals and explained variance

    Chemometrics and Intelligent Laboratory Systems, Vol. 196

  3. Multivariate Exploratory Data Analysis Using Component Models

    Comprehensive Foodomics (Elsevier), pp. 241-268

2019

  1. Semi-supervised multivariate statistical network monitoring for learning security threats

    IEEE Transactions on Information Forensics and Security, Vol. 14, Núm. 8, pp. 2179-2189

2018

  1. Group-wise ANOVA simultaneous component analysis for designed omics experiments

    Metabolomics, Vol. 14, Núm. 6

  2. Group-wise partial least square regression

    Journal of Chemometrics, Vol. 32, Núm. 3

2017

  1. Group-Wise Principal Component Analysis for Exploratory Data Analysis

    Journal of Computational and Graphical Statistics, Vol. 26, Núm. 3, pp. 501-512

2015

  1. Determining the number of components in principal components analysis: A comparison of statistical, crossvalidation and approximated methods

    Chemometrics and Intelligent Laboratory Systems, Vol. 149, pp. 99-116

  2. On the use of the observation-wise k-fold operation in PCA cross-validation

    Journal of Chemometrics, Vol. 29, Núm. 8, pp. 467-478