Blar i Institutt for elektro, IT, og kybernetikk på emneord "PLSR"

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    • Noise handling capabilities of multivariate methods 

      Ergon, Rolf (Journal article; Peer reviewed, 2002)
      The noise handling capabilities of principal component regression (PCR) and partial least squares regression (PLSR) are somewhat disputed issues, especially regarding regressor noise. In an attempt to indicate an answer ...

    • Re-interpretation of NIPALS results solves PLSR inconsistency problem 

      Ergon, Rolf (Journal article; Peer reviewed, 2009)
      The well-known nonlinear iterative partial least squares (NIPALS) algorithm is commonly used for computation of components in partial least squares regression (PLSR) with orthogonalized score vectors. Based on generalized ...

    • Reduced PCR/PLSR models by subspace projections 

      Ergon, Rolf (Journal article; Peer reviewed, 2006)
      Latent variables models used in principal component regression (PCR) or partial least squares regression (PLSR) often use a high number of components, and this makes interpretation of score and loading plots difficult. ...