Full text
| |
| Author(s): |
Bruno Ramos dos Santos
Total Authors: 1
|
| Document type: | Doctoral Thesis |
| Press: | São Paulo. |
| Institution: | Universidade de São Paulo (USP). Instituto de Matemática e Estatística (IME/SBI) |
| Defense date: | 2016-04-29 |
| Examining board members: |
Heleno Bolfarine;
Marcia D Elia Branco;
Victor Hugo Lachos Davila;
Jorge Luis Bazán Guzmán;
Vera Lucia Damasceno Tomazella
|
| Advisor: | Heleno Bolfarine |
| Abstract | |
This thesis aims to propose extensions of Bayesian quantile regression models, considering proportion data with zero inflation, and also censored data at zero. Initially, it is suggested an analysis of influential observations, based on the location-scale mixture representation of the asymmetric Laplace distribution, where the posterior distribution of the latent variables are compared with the goal of identifying possible outlying observations. Next, a two-part model is proposed to analyze proportion data with zero or one inflation, studying the conditional quantile and the probability of the response variable being equal to zero. Following, Bayesian quantile regression models are proposed for continuous data with a discrete component at zero, where part of these observations are assumed censored. These models may be considered more complete in the analysis of this type of data, as the censoring probability varies with the quantiles of interest. For last, it is considered an application of these models with spacial correlation, in order to study the data about the last presidential election in Brazil in 2014. In this example, the quantile regression models are able to incorporate spatial dependence with the asymmetric Laplace process. For all the proposed models it was developed a R package, which is exemplified in the appendix. (AU) | |
| FAPESP's process: | 12/20267-9 - Extensions of Bayesian quantile regression models |
| Grantee: | Bruno Ramos dos Santos |
| Support Opportunities: | Scholarships in Brazil - Doctorate |