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A Parametric Quantile Regression Model for Asymmetric Response Variables on the Real Line
| Content Provider | MDPI |
|---|---|
| Author | Gómez, Héctor W. Gallardo, Diego I. Bourguignon, Marcelo Galarza, Christian E. |
| Copyright Year | 2020 |
| Description | In this paper, we introduce a novel parametric quantile regression model for asymmetric response variables, where the response variable follows a power skew-normal distribution. By considering a new convenient parametrization, these distribution results are very useful for modeling different quantiles of a response variable on the real line. The maximum likelihood method is employed to estimate the model parameters. Besides, we present a local influence study under different perturbation settings. Some numerical results of the estimators in finite samples are illustrated. In order to illustrate the potential for practice of our model, we apply it to a real dataset. |
| Starting Page | 1938 |
| e-ISSN | 20738994 |
| DOI | 10.3390/sym12121938 |
| Journal | Symmetry |
| Issue Number | 12 |
| Volume Number | 12 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2020-11-25 |
| Access Restriction | Open |
| Subject Keyword | Symmetry Mathematical Social Sciences Statistics and Probability Asymmetric Data Parametric Inference Quantile Regression Model Skew-normal Distributions |
| Content Type | Text |
| Resource Type | Article |
