| Full text | |
| Author(s): |
Galarza Morales, Christian E.
;
Lachos, Victor H.
;
Bourguignon, Marcelo
Total Authors: 3
|
| Document type: | Journal article |
| Source: | STAT; v. 10, n. 1, p. 15-pg., 2021-12-01. |
| Abstract | |
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) | |
| FAPESP's process: | 18/11580-1 - Moments of doubly truncated multivariate distributions |
| Grantee: | Christian Eduardo Galarza Morales |
| Support Opportunities: | Scholarships abroad - Research Internship - Doctorate |
| FAPESP's process: | 15/17110-9 - Robust Estimation in Spatial Models for Censored Data |
| Grantee: | Christian Eduardo Galarza Morales |
| Support Opportunities: | Scholarships in Brazil - Doctorate |