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| Puiatti,Guilherme Alves; Cecon,Paulo Roberto; Nascimento,Moysés; Nascimento,Ana Carolina Campana; Carneiro,Antônio Policarpo Souza; Silva,Fabyano Fonseca e; Puiatti,Mário; Cruz,Cosme Damião. |
| ABSTRACT: The objective of this study was to adjust nonlinear quantile regression models for the study of dry matter accumulation in garlic plants over time, and to compare them to models fitted by the ordinary least squares method. The total dry matter of nine garlic accessions belonging to the Vegetable Germplasm Bank of Universidade Federal de Viçosa (BGH/UFV) was measured in four stages (60, 90, 120 and 150 days after planting), and those values were used for the nonlinear regression models fitting. For each accession, there was an adjustment of one model of quantile regression (τ=0.5) and one based on the least squares method. The nonlinear regression model fitted was the Logistic. The Akaike Information Criterion was used to evaluate the goodness of... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Quantile regression; Nonlinear regression; Allium sativum L.; Growth rate; Cluster analysis.. |
| Ano: 2020 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782020000100203 |
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| Puiatti,Guilherme Alves; Cecon,Paulo Roberto; Nascimento,Moysés; Nascimento,Ana Carolina Campana; Carneiro,Antônio Policarpo Souza; Silva,Fabyano Fonseca e; Puiatti,Mário; Oliveira,Ana Carolina Ribeiro de. |
| ABSTRACT: Plant growth analyses are important because they generate information on the demand and necessary care for each development stage of a plant. Nonlinear regression models are appropriate for the description of curves of growth, since they include parameters with practical biological interpretation. However, these models present information in terms of the conditional mean, and they are subject to problems in the adjustment caused by possible outliers or asymmetry in the distribution of the data. Quantile regression can solve these problems, and it allows the estimation of different quantiles, generating more complete and robust results. The objective of this research was to adjust a nonlinear quantile regression model for the study of dry matter... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Quantile regression; Nonlinear regression; Dry matter; Allium sativum L. |
| Ano: 2018 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-84782018000100203 |
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| Macedo,Leandro Roberto de; Cecon,Paulo Roberto; Silva,Fabyano Fonseca e; Nascimento,Moysés; Puiatti,Guilherme Alves; Oliveira,Ana Carolina Ribeiro de; Puiatti,Mario. |
| Abstract: The objective of this work was to identify nonlinear regression models that best describe dry matter accumulation curves over time, in garlic (Allium sativum) accessions, using Bayesian and frequentist approaches. Multivariate cluster analyses were made to group similar accessions according to the estimates of the parameters with biological interpretation (β1 and β3). In order to verify if the obtained groups were equal, statistical tests were applied to assess the parameter equality of the representative curves of each group. Thirty garlic accessions were used, which are kept by the vegetable germplasm bank of Universidade Federal de Viçosa, Brazil. The logistic model was the one that fit best to data in both approaches. Parameter estimates of... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Allium sativum; Cluster analysis; Multivariate clustering curves; Nonlinear models. |
| Ano: 2017 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2017000800572 |
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