Structural components in functional data. [PDF]
, 2009 Analyzing functional data often leads to finding common factors, for which functional principal component analysis proves to be a useful tool to summarize and characterize the random variation in a function space.
Gasser, Theo +2 more
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Population structure identification of Turkmen and Darehshori horses using PCA, DAPC, and SPC methods [PDF]
مجله بیوتکنولوژی کشاورزی, 2022 ObjectiveConservation of the genetic diversity of indigenous animals is very important. For the sustainable use of genetic resources, it is necessary to first study the genetic structure of populations.
Ghazaleh Javanmard +5 more
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Investigation of Morphological Diversity and Evaluation of Tomato Lines Yield Using Multivariate Statistical Analysis [PDF]
Majallah-i ̒Ulum-i Bāghbānī, 2022 Introduction Tomato is a product with a wide range of genotypes with different yields and selection based on this trait and its components can accelerate the breeding programs of this plant.
S. Golcheshmeh +3 more
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FACIAL EXPRESSION RECOGNITION BASED ON PRINCIPAL COMPONENTS ANALYSIS [PDF]
International Journal of Intelligent Computing and Information Sciences, 2016 Recognizing facial expression is one of the most effective applications of image processing and has obtained great attention in latest years. A recognition system for facial expression is a computer based application which detects an individual facial ...
A. Hewa, O. Nomir, A. Saleh
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Identification of dietary patterns by principal component analysis in schoolchildren in the South of Brazil and associated factors [PDF]
Revista Brasileira de Saúde Materno Infantil, 2020 Objectives: to identify dietary patterns (DP) and associated factors in first grade school-children in elementary schools in the South of Brazil. Methods: school-based cross-sectional study, with a non-probabilistic sample of 782 schoolchildren aged 6 ...
Gabriela Rodrigues Bratkowski +3 more
doaj +4 more sources
ANOVA bootstrapped principal components analysis for logistic regression
Croatian Review of Economic, Business and Social Statistics, 2022 Principal components analysis (PCA) is often used as a dimensionality reduction technique. A small number of principal components is selected to be used in a classification or a regression model to boost accuracy.
Toleva Borislava
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COPD phenotype description using principal components analysis
Respiratory Research, 2009 Background Airway inflammation in COPD can be measured using biomarkers such as induced sputum and FeNO. This study set out to explore the heterogeneity of COPD using biomarkers of airway and systemic inflammation and pulmonary function by principal ...
Vestbo Jørgen +5 more
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Using Principal Components Analysis in Program Evaluation: Some Practical Considerations
Journal of MultiDisciplinary Evaluation, 2006 Principal Components Analysis (PCA) is widely used by behavioral science researchers to assess the dimensional structure of data and for data reduction purposes.
J. Thomas Kellow
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Remote Sensing, 2022 Recently, Jia et al. employed the index, modified remote sensing ecological index (MRSEI), to evaluate the ecological quality of the Qaidam Basin, China. The MRSEI made a modification to the previous remote sensing-based ecological index (RSEI), which is
Hanqiu Xu +3 more
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Principal Components Analysis Utility in the Livestock Field
Bulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca. Animal Science and Biotechnologies, 2016 Principal Component Analysis is a method factor - factor analysis - and is used to reduce data complexity by replacingmassive data sets by smaller sets.
Ancuta Simona Rotaru +3 more
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