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American cutaneusleishmaniasisprofi le in a braziliamSouthwestern Amazonia: a multivariate approach
(Univ Santa Cruz Do Sul, 2018-01-01)
Background and Objectives: The American Cutaneous Leishmaniasis (ACL) is a disease of complex chain of transmission subject to various determinants, in the same region. Theaim was to analyze the ACL behavior and identify ...
Application of k-means clustering, linear discriminant analysis and multivariate linear regression for the development of a predictive QSAR model on 5-lipoxygenase inhibitors
(Elsevier Science, 2015-04)
In this work, we performed a quantitative structure activity relationship (QSAR) model for a family of 5-lipoxygenase (5-LOX) inhibitors using k-means clustering and linear discriminant analysis (LDA) for the selection of ...
Genetic diversity in table grapes based on RAPD and microsatellite markers.
(Pesquisa agropecuária Brasileira, Brasília, v.46, n.9, p.1035-1044, set. 2011, 2011)
The effective sample size for multivariate spatial processes with an application to soil contamination
(2021)
Effective sample size accounts for the equivalent number of independent observations contained in a sample of correlated data. This notion has been widely studied in the context of univariate spatial variables. In that ...
Multivariate analysis to research innovation complementarities
(Taylor & Francis, 2017-10)
It is widely recognized that orthodox economics is obsessed with econometrics tools. However, econometrics techniques have a limited capacity to deal with qualitative variables coming from surveys. This paper presents a ...
Identification of superior genotypes and soybean traits by multivariate analysis and selection index
(2018-07-01)
The selection of superior genotypes of soybean is a complex process, thus exploratory multivariate techniques can be applied to select genotypes analyzing the agronomic traits altogether, increasing the chance of success ...
Cluster analysis using multivariate mixed effects models
(WILEY, 2009)