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Mean estimation with data missing at random for functional covariables
(Taylor & Francis, 2013-08)
In a missing-data setting, we want to estimate the mean of a scalar outcome, based on a sample in which an explanatory variable is observed for every subject while responses are missing by happenstance for some of them. ...
Técnica de identificação de modelos lineares e não-lineares de séries temporais
(Sociedade Brasileira de Automática, 2006)
Mapeamento explícito como Kernel em aprendizado de máquinas de vetores de suporte
(Universidade Federal de Minas GeraisUFMG, 2015-02-12)
The problems that can be solved through the machine learning approach also have influence on particularities of the implemented algorithms, they are divided in three large groups: regression, classification and clustering. ...
Comparison between linear and non-parametric regression models for genome-enabled prediction in wheat
(Genetics Society of Americahttp://www.g3journal.org/content/2/12/1595.full, 2013)
Non-Parametric Pricing of Interest Rates OptionsNon-Parametric Pricing of Interest Rates Options
(Sociedade Brasileira de Econometria, 2012)
Functional form estimation using oblique projection matrices for ls-SVM regression models
Kernel regression models have been used as non-parametric methods for fitting experimental data. However, due to their non-parametric nature, they belong to the so-called 'black box' models, indicating that the relation ...
Genome-enabled prediction of genetic values using radial basis function neural networks
(Springerhttps://link.springer.com/article/10.1007%2Fs00122-012-1868-9, 2013)
Regressão binomial negativa geograficamente ponderada : modelando superdispersão espacial
(2012-05-01)
A regressão global pressupõe que um modelo único é adequado para descrever todas as partes de uma região de estudo. No entanto, a força dos relacionamentos entre as variáveis pode não ser espacialmente constante. Além ...
Semiparametric smoothing spline to joint mean and variance models with responses from the biparametric exponential family: a bayesian perspective
(Universidad Nacional de ColombiaBogotá - Ciencias - Doctorado en Ciencias - EstadísticaDepartamento de EstadísticaFacultad de CienciasBogotá, ColombiaUniversidad Nacional de Colombia - Sede Bogotá, 2022-01)
Statistical applications need to address an increasing complexity due to new data arising from recent technologies, new phenomenons, and diverse sources of uncertainty. The demand for flexible methods with non-standard ...