lqr: Robust Linear Quantile Regression
It fits a robust linear quantile regression model using a new
family of zero-quantile distributions for the error term. Missing values and censored observations can be handled as well. This family of
distribution includes skewed versions of the Normal, Student's t, Laplace, Slash
and Contaminated Normal distribution. It also performs logistic quantile regression for bounded responses
as shown in Galarza et.al.(2020) <doi:10.1007/s13571-020-00231-0>. It provides estimates and full inference.
It also provides envelopes plots for assessing the fit and confidences bands
when several quantiles are provided simultaneously.
| Version: |
3.31 |
| Imports: |
graphics, stats, spatstat, numDeriv, MomTrunc, quantreg |
| Suggests: |
ald, qrLMM, qrNLMM |
| Published: |
2020-10-13 |
| Author: |
Christian E. Galarza, Luis Benites, Marcelo Bourguignon, Victor H. Lachos |
| Maintainer: |
Christian E. Galarza <cgalarza88 at gmail.com> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
no |
| CRAN checks: |
lqr results |
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Reverse dependencies:
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