Opened Access Modelo PLS
Estadísticas
Icon
Exportar a
Autor: Espejo Alonso, Lucía
Director: Pino Mejías, Rafael
Departamento: Universidad de Sevilla. Departamento de Estadística e Investigación Operativa
Fecha: 2017-06
Tipo de documento: Trabajo Fin de Master
Titulación: Universidad de Sevilla. Máster Universitario en Matemáticas
Resumen: The Partial Least Squares approach (PLS) is a multivariate technique which was originated around 1975 by Herman Wold for the modelling of complicated data sets in terms of chains of matrices (blocks), the so-called path model. This included a simple but efficient way to estimate the parameters in these models called NIPALS (non-linear iterative partial least squares). Around 1980, the simplest PLS model with two blocks (X, set of predictor variables, and Y, set of response variables) was slightly modified by his son Svante Wold and Hararld Martes to better suit to data from science and technology, and it was proved to be useful to deal with complicated data sets where ordinary regression was difficult or impossible to apply. Partial Least Squares Regression (PLSR) solves the problem that arises when there are many predictor variables with an extreme dependency relation (multicollinearity problem). For this, PLSR finds a set of new variables which are created as a linear combination of...
[Ver más]
Tamaño: 1.210Mb
Formato: PDF

URI: http://hdl.handle.net/11441/63227

Mostrar el registro completo del ítem


Esta obra está bajo una Licencia Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 Internacional

Este registro aparece en las siguientes colecciones