Please use this identifier to cite or link to this item:
http://hdl.handle.net/10773/35510
Title: | Censored multivariate linear regression model |
Author: | Pereira, Isabel Sousa, Rodney Silva, Maria Eduarda |
Keywords: | Censored Data Multivariate Linear Regression |
Issue Date: | 29-Nov-2022 |
Publisher: | Springer |
Abstract: | Often, real life problems require modelling several response variables together. This work analyses multivariate linear regression model when the data are censored. Censoring distorts the correlation structure of the underlying variables and increases the bias of the usual estimators. Thus, we propose three methods to deal with multivariate data under left censoring, namely, Expectation Maximization (EM), Data Augmen- tation (DA) and Gibbs Sampler with Data Augmentation (GDA). Re- sults from a simulation study show that both, DA and GDA estimates are consistent for low and moderate correlation. |
Peer review: | yes |
URI: | http://hdl.handle.net/10773/35510 |
DOI: | 10.1007/978-3-031-12766-3_20 |
ISBN: | 978-3-031-12765-6 |
Publisher Version: | https://link.springer.com/chapter/10.1007/978-3-031-12766-3_20 |
Appears in Collections: | CIDMA - Capítulo de livro PSG - Capítulo de livro |
Files in This Item:
File | Description | Size | Format | |
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spe2021_009.pdf | 333.56 kB | Adobe PDF | View/Open |
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