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Comments on 'Observed trends in Indices of Daily Temperature extremes in South America 1960-2000'
(Journal of Climate, 2011)
Robust and sparse estimators for linear regression models
(Elsevier Science, 2017-07)
Penalized regression estimators are popular tools for the analysis of sparse and high-dimensional models. However, penalized regression estimators defined using an unbounded loss function can be very sensitive to the ...
Crop yield estimation using satellite images: comparison of linear and non-linear models
(Facultad de Ciencias Agropecuarias., 2018)
Robust estimators in partly linear regression models on Riemannian manifolds
(Taylor, 2014)
Under a partly linear model we study a family of robust estimates for the regression parameter and the regression function when some of the predictors take values on a Riemannian manifold. We obtain the consistency and the ...
Uso de técnicas de regressão na avaliação, em bovinos de corte, da eficiência de conversão do alimento em produto: proposição de método e significância nutricionalUse of regression techniques in the evaluation, in beef cattle, of feed conversion into product: proposition of method and nutritional significance
(Sociedade Brasileira de Zootecnia (SBZ), 2020)
Comparação de métodos de estimação em um modelo linear simples com erro nas variáveis
(Universidade Federal de Santa Maria, 2017)
Studying bloat control and maintenance of effective code in linear genetic programming for symbolic regression
(Elsevier Science Bv, 2016)
Linear Genetic Programming (LGP) is an Evolutionary Computation algorithm, inspired in the Genetic Programming (GP) algorithm. Instead of using the standard tree representation of GP, LGP evolves a linear program, which ...
A fast electric load forecasting using neural networks
(2000-12-01)
The objective of this work is the development of a methodology for electric load forecasting based on a neural network. Here, it is used Backpropagation algorithm with an adaptive process based on fuzzy logic. This methodology ...