Browsing NOFIMA vitenarkiv by Journals "Journal of Chemometrics"
Now showing items 1-13 of 13
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A similarity index for comparing coupled matrices
(Journal article; Peer reviewed, 2018) -
Baseline and interferent correction by the Tikhonov regularization framework for linear least squares modeling
(Journal article; Peer reviewed, 2018) -
Combining analysis of variance and three-way factor analysis methods for studying additive and multiplicative effects in sensory panel data
(Peer reviewed; Journal article, 2015)Data from descriptive sensory analysis are essentially three-way data with assessors, samples and attributes as the three ways in the data set. Because of this, there are several ways that the data can be analysed. The ... -
Combining analysis of variance and three-way factor analysis methods for studying additive and multiplicative effects in sensory panel data
(Peer reviewed; Journal article, 2015)Data from descriptive sensory analysis are essentially three-way data with assessors, samples and attributes as the three ways in the data set. Because of this, there are several ways that the data can be analysed. The ... -
Common and distinct components in data fusion
(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 ... -
Confidence ellipsoids for ASCA models based on multivariate regression theory
(Journal article; Peer reviewed, 2018) -
Diagnosing indirect relationships in multivariate calibration models
(Peer reviewed; Journal article, 2021)Problems concerning covariance among independent variables are well understood and dealt with by inverse regression methods like partial least squares regression. However, covariance between dependent variables has only ... -
Dynamic Multiblock Regression for Process Modelling
(Peer reviewed; Journal article, 2024)The study introduces three novel strategies for incorporating capabilities for dynamic modelling into multiblock regression methods by integrating sequentially orthogonalised partial least squares (SO-PLS) with different ... -
Making sense of multiple distance matrices through common and distinct components
(Peer reviewed; Journal article, 2021)Multiblock analysis attacks the problem of how to combine data from various data sources for purposes such as prediction, classification, clustering, or visual data analysis. A key concept is the distinction between “common” ... -
Performance of methods that separate common and distinct variation in multiple data blocks
(Journal article; Peer reviewed, 2018) -
Selecting the number of factors in principal component analysis by permutation testing—Numerical and practical aspects
(Journal article; Peer reviewed, 2017)Selecting the correct number of factors in principal component analysis (PCA) is a critical step to achieve a reasonable data modelling, where the optimal strategy strictly depends on the objective PCA is applied for. In ... -
Selection of principal variables through a modified Gram–Schmidt process with and without supervision
(Peer reviewed; Journal article, 2023)In various situations requiring empirical model building from highly multivariate measurements, modelling based on partial least squares regression (PLSR) may often provide efficient low-dimensional model solutions. In ... -
Sequential and orthogonalized PLS (SO-PLS) regression for path analysis: Order of blocks and relations between effects
(Peer reviewed; Journal article, 2020)This paper is about the use of the multiblock regression method sequential and orthogonalized partial least squares (SO-PLS) for path modeling. The paper is a follow up of previously published papers on the same topic and ...