Now showing items 1-10 of 2581
The use of principal components and univariate charts to control multivariate processes
In this article, we evaluate the performance of the T2 chart based on the principal components (PC chart) and the simultaneous univariate control charts based on the original variables (SU X̄ charts) or based on the principal ...
Hydrological responses in equatorial watersheds indicated by Principal Components Analysis (PCA) - study case in Atrato River Basin (Colombia)
(Assoc Brasileira Recursos Hidricos-abrh, 2020-01-01)
The Atrato river basin is located in the Pacific fringe of Colombia, region with one of the highest precipitation rates in the world. The main purpose of this study is to determine the dominant processes in the hydrological ...
Relationship between wheat flour properties and french bread char- acteristics using principal component analysis
(Research Journal Biotechnology, 2015-04)
The objective was to use Principal Component Analysis as a tool to assess the relationship between physical and rheological characteristics of wheat flour and the quality of french bread. Flours belonging to eight varieties ...
Principal component analysis for selection of superior maize genotypesAnálise de componentes principais para seleção de genótipos superiores de milho
Constant advances in studies on the behavior of maize genotypes and their interactions with the environment are of great importance for the best performance of the plant. This study verifies effects and causes of agronomic ...
Influence function of projection-pursuit principal components for functional data
(Elsevier Inc, 2015-01)
In the finite-dimensional setting, Li and Chen (1985) proposed a method for principal components analysis using projection-pursuit techniques. This procedure was generalized to the functional setting by Bali et al. (2011), ...
On the asymptotic behavior of general projection-pursuit estimators under the common principal components model
(Elsevier Science, 2010-02)
The common principal components model for several groups of multivariate observations assumes equal principal axes among the groups. Robust estimators can be defined replacing the sample variance by a robust dispersion ...
A partial least squares and principal component regression study of quinone compounds with trypanocidal activity
A quantitative structure-activity relationship (QSAR) study of 19 quinone compounds with trypanocidal activity was performed by Partial Least Squares (PLS) and Principal Component Regression (PCR) methods with the use of ...
Conformational analysis: A new approach by means of chemometrics
Robust estimators under a functional common principal components model
(Elsevier Science, 2017-09)
When dealing with several populations of functional data, equality of the covariance operators is often assumed even when seeking for a lower-dimensional approximation to the data. Usually, if this assumption does not hold, ...
Detecting influential observations in principal components and common principal components
(Elsevier Science, 2010-12)
Detecting outlying observations is an important step in any analysis, even when robust estimates are used. In particular, the robustified Mahalanobis distance is a natural measure of outlyingness if one focuses on ellipsoidal ...