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Short-term multinodal load forecasting in distribution systems using general regression neural networks
(2011-10-05)
Multinodal load forecasting deals with the loads of several interest nodes in an electrical network system, which is also known as bus load forecasting. To perform this demand, it is necessary a technique that is precise, ...
Short-term multinodal load forecasting in distribution systems using general regression neural networks
(2011-10-05)
Multinodal load forecasting deals with the loads of several interest nodes in an electrical network system, which is also known as bus load forecasting. To perform this demand, it is necessary a technique that is precise, ...
Robust estimation in partially linear regression models with monotonicity constraints
(Taylor & Francis, 2019-11)
Partially linear models are important tools in statistical modelling, combining the flexibility of non–parametric models and the simple interpretation of linear models. Monotonicity constraints appear naturally in certain ...
Ultrastructure of spermatogenesis, spermatozoon and processes of testicular regression and recrudescence in Eptesicus furinalis (Chiroptera: Vespertilionidae)
(Elsevier B.V., 2014-08-01)
Studies have shown that the annual reproductive cycle of Eptesicus furinalis includes at least one period of total testicular regression. Thus, this study aimed to evaluate their reproductive cycle ultrastructurally. The ...
Modeling variability in generalized linear models
This work proposes joint modeling of parameters in the biparametric exponential family, including heteroscedastic linear regression (non linear regression) models; with joint modeling of the mean and precision (the ...
Asymmetric Laplace Regression: Maximum Likelihood, Maximum Entropy and Quantile Regression
(De Gruyter, 2016-01)
This paper studies the connections among the asymmetric Laplace probability density (ALPD), maximum likelihood, maximum entropy and quantile regression. We show that the maximum likelihood problem is equivalent to the ...
Ordinary regression and orthogonal regression in the plane
(Wolfram Demonstration Project, 2011)
Ordinary regression and orthogonal regression in the plane
(Wolfram Demonstration Project, 2016)
Breeding value accuracy estimates for growth traits using random regression and multi-trait models in Nelore cattle
(Funpec-editora, 2011-01-01)
We quantified the potential increase in accuracy of expected breeding value for weights of Nelore cattle, from birth to mature age, using multi-trait and random regression models on Legendre polynomials and B-spline ...