Mostrando ítems 1-10 de 5328
Neural networks as an optimization tool for regression
(Universidade Federal de São CarlosUFSCarPrograma Interinstitucional de Pós-Graduação em Estatística - PIPGEsCâmpus São Carlos, 2019-09-02)
Neural networks are a tool to solve prediction problems that have gained much prominence recently. In general, neural networks are used as a predictive method, that is, their are used to estimate a regression function. ...
Contribuições em modelos de regressão com erro de medida multiplicativo
(Universidade Federal de São CarlosUFSCarPrograma Interinstitucional de Pós-Graduação em Estatística - PIPGEsCâmpus São Carlos, 2016-02-04)
In regression models in which a covariate is measured with error, it is common
to use structures that correlate the observed covariate with the true non-observed
covariate. Such structures are usually additive or ...
Modelos preditivos para LGD
(Universidade Federal de São CarlosUFSCarPrograma Interinstitucional de Pós-Graduação em Estatística - PIPGEsCâmpus São Carlos, 2018-05-04)
Financial institutions willing to use the advanced Internal Ratings Based (IRB) need to develop
methods to estimate the LGD (Loss Given Default) risk component. Proposals for PD (Probability
of default) modeling have ...
Penalized regression methods for compositional data
(Universidade Federal de São CarlosUFSCarPrograma Interinstitucional de Pós-Graduação em Estatística - PIPGEsCâmpus São Carlos, 2018-12-10)
Compositional data consist of known vectors such as compositions whose components are positive and defined in the interval (0,1) representing proportions or fractions of a "whole", where the sum of these components must ...
Comparação de métodos de estimação para problemas com colinearidade e/ou alta dimensionalidade (p > n)
(Universidade Federal de São CarlosUFSCarPrograma Interinstitucional de Pós-Graduação em Estatística - PIPGEsCâmpus São Carlos, 2016-04-29)
This paper presents a comparative study of the predictive power of four suitable regression
methods for situations in which data, arranged in the planning matrix, are very
poorly multicolinearity and / or high dimensionality, ...
Hacia una nueva propuesta en la selección de familias del Programa Chile Solidario: aplicación de Multivariate Adaptive Regression Splines (MARS) y Análisis Discriminante Basado en Distancias (DB)t
(Universidad de Chile, 2011)
Objetivo general: Generar un modelo de discriminación explicito usando la metodología Multivariate Adaptive Regression Splines (MARS) para la selección de
beneficiarios del Programa Chile Solidario, y comparar las ...
A Multivariate Regression Model Between the October Rainfall Anomalies in Central America and the Tropical Pacific and Atlantic Ocean
(1999-11)
Principal Component Analysis was used to identity common anomaly patterns amongst 72 rainfall gauge stations in Central America during October, in order to identify stations to from October Rainfall Indices. October was ...
Uma proposta contextualizada para o ensino médio: regressão linear
(Universidade Federal de São CarlosUFSCarPrograma de Pós-Graduação em Ensino de Ciências Exatas - PPGECECâmpus São Carlos, 2019-01-25)
This work has as the main objective the teaching of Linear Regression contextualized to High School students. For this, it was elaborated a plan of teaching unity which has four class plans. The class plans are structured ...