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Comparison of Regression and Neural Networks Models to Estimate Solar Radiation
(Instituto de Investigaciones Agropecuarias, INIA, 2010)
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 ...
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 ...
Estimation of spontaneous blinking main sequence in normal subjects and patients with Graves' upper eyelid retraction
(2013-02-01)
Purpose. We quantified the main sequence of spontaneous blinks in normal subjects and Graves' disease patients with upper eyelid retraction using a nonlinear and two linear models, and examined the variability of the main ...
Robust estimators in semi-functional partial linear regression models
(Elsevier Inc, 2017-02)
Partial linear models have been adapted to deal with functional covariates to capture both the advantages of a semi-linear modelling and those of nonparametric modelling for functional data. It is easy to see that the ...
Non-destructive equations to estimate the leaf area of Styrax pohlii and Styrax ferrugineus
(Instituto Internacional de Ecologia, 2014-02-01)
We developed linear equations to predict the leaf area (LA) of the species Styrax pohlii and Styrax ferrugineus using the width (W) and length (L) leaf dimensions. For both species the linear regression (Y=α+bX) using LA ...
Quantile Regression In Linear Mixed Models: A Stochastic Approximation Em Approach
(Int Press Boston, IncSomerville, 2017)
Measuring time series predictability using support vector regression
(TAYLOR & FRANCIS INC, 2008)
Most studies involving statistical time series analysis rely on assumptions of linearity, which by its simplicity facilitates parameter interpretation and estimation. However, the linearity assumption may be too restrictive ...
Partially linear censored regression models using heavy-tailed distributions: A Bayesian approach
(Elsevier Science BvAmsterdamHolanda, 2014)
GIS-based analytical tools for transport planning: spatial regression models for transportation demand forecast
(2014)
Considering the importance of spatial issues in transport planning, the main objective of this study was to analyze the results obtained from different approaches of spatial regression models. In the case of spatial ...