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Master's Dissertation
DOI
https://doi.org/10.11606/D.45.2019.tde-20052019-132652
Document
Author
Full name
Kévin Allan Sales Rodrigues
E-mail
Institute/School/College
Knowledge Area
Date of Defense
Published
São Paulo, 2019
Supervisor
Committee
Elian, Silvia Nagib (President)
Artes, Rinaldo
Pereira, Gustavo Henrique de Araujo
Title in Portuguese
Diagnóstico em regressão L1
Keywords in Portuguese
Likelihood displacement
Medidas de Influência
Métodos de diagnóstico
Regressão L1
Regressão robusta
Abstract in Portuguese
Este texto apresenta um método alternativo de regressão que é denominado regressão L1. Este método é robusto com relação a outliers na variável Y enquanto o método tradicional, mínimos quadrados, não oferece robustez a este tipo de outlier. Neste trabalho reanalisaremos os dados sobre imóveis apresentados por Narula e Wellington (1977) à luz da regressão L1. Ilustraremos os principais resultados inferenciais como: interpretação do modelo, construção de intervalos de confiança e testes de hipóteses para os parâmetros, análise de medidas de qualidade do ajuste do modelo e também utilizaremos medidas de diagnóstico para destacar observações influentes. Dentre as medidas de influência utilizaremos a diferença de verossimilhanças e a diferença de verossimilhanças condicional.
Title in English
Diagnostic in L1 regression
Keywords in English
Diagnostic methods
Influence measures
LAD regression
Likelihood displacement
Robust regression
Abstract in English
This text presents an alternative method of regression that is called L1 regression. This method is robust to outliers in the Y variable while the traditional least squares method does not provide robustness to this type of outlier. In this work we will review the data about houses presented by Narula and Wellington (1977) in the light of the L1 regression. We will illustrate the main inferential results such as: model interpretation, construction of confidence intervals and hypothesis tests for the parameters, analysis of quality measures of model fit and also use diagnostic measures to highlight influential observations. Among the measures of influence we will use the likelihood displacement and the conditional likelihood displacement.
 
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Publishing Date
2019-05-28
 
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