Blar i NOFIMA vitenarkiv på forfatter "Bro, Rasmus"

Viser treff 1-4 av 4

    • Common and distinct components in data fusion 

      Smilde, Age K.; Måge, Ingrid; Næs, Tormod; Hankemeier, Thomas; Lips, Miriam B.; Kiers, Henk A. L.; Acar, Evrim; Bro, Rasmus (Journal article; Peer reviewed, 2017)
      In many areas of science, multiple sets of data are collected pertaining to the same system. Examples are food products that are characterized by different sets of variables, bioprocesses that are online sampled with ...

    • Extension of SO-PLS to multi-way arrays: SO-N-PLS 

      Biancolillo, Alessandra; Næs, Tormod; Bro, Rasmus; Måge, Ingrid (Journal article; Peer reviewed, 2017)
      Multi-way data arrays are becoming more common in several fields of science. For instance, analytical instruments can sometimes collect signals at different modes simultaneously, as e.g. fluorescence and LC/GC-MS. Higher ...

    • Variable selection in multi-block regression 

      Biancolillo, Alessandra; Liland, Kristian Hovde; Måge, Ingrid; Næs, Tormod; Bro, Rasmus (Journal article, 2016)
      The focus of the present paper is to propose and discuss different procedures for performing variable selection in a multi-block regression context. In particular, the focus is on two multi-block regression methods: ...

    • Why use component-based methods in sensory science? 

      Næs, Tormod; Varela, Paula; Castura, John C.; Bro, Rasmus; Tomic, Oliver (Peer reviewed; Journal article, 2023)
      This paper discusses the advantages of using so-called component-based methods in sensory science. For instance, principal component analysis (PCA) and partial least squares (PLS) regression are used widely in the field; ...