| Texto completo | |
| Autor(es): |
Galarza Morales, Christian E.
;
Lachos, Victor H.
;
Bourguignon, Marcelo
Número total de Autores: 3
|
| Tipo de documento: | Artigo Científico |
| Fonte: | STAT; v. 10, n. 1, p. 15-pg., 2021-12-01. |
| Resumo | |
Quantile regression has emerged as an important analytical alternative to the classical mean regression model. However, the analysis could be complicated by the presence of censored measurements due to a detection limit of equipment in combination with unavoidable missing values arising when, for instance, a researcher is simply unable to collect an observation. Another complication arises when measures depart significantly from normality, for instance, in the presence of skew heavy-tailed observations. For such data structures, we propose a robust quantile regression for censored and/or missing responses based on the skew-t distribution. A computationally feasible EM-based procedure is developed to carry out the maximum likelihood estimation within such a general framework. Moreover, the asymptotic standard errors of the model parameters are explicitly obtained via the information-based method. We illustrate our methodology by using simulated data and two real data sets. (AU) | |
| Processo FAPESP: | 18/11580-1 - Momentos de distribuições multivariadas duplamente truncadas |
| Beneficiário: | Christian Eduardo Galarza Morales |
| Modalidade de apoio: | Bolsas no Exterior - Estágio de Pesquisa - Doutorado |
| Processo FAPESP: | 15/17110-9 - Estimação Robusta em Modelos Espaciais para Dados Censurados. |
| Beneficiário: | Christian Eduardo Galarza Morales |
| Modalidade de apoio: | Bolsas no Brasil - Doutorado |