quantreg.nonpar
Nonparametric Series Quantile Regression
Implements the nonparametric quantile regression method developed by Belloni, Chernozhukov, and Fernandez-Val (2011) to partially linear quantile models. Provides point estimates of the conditional quantile function and its derivatives based on series approximations to the nonparametric part of the model. Provides pointwise and uniform confidence intervals using analytic and resampling methods.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
1.0 |
rolling linux/jammy R-4.5 | quantreg.nonpar_1.0.tar.gz |
800.3 KiB |
1.0 |
rolling linux/noble R-4.5 | quantreg.nonpar_1.0.tar.gz |
800.4 KiB |
1.0 |
rolling source/ R- | quantreg.nonpar_1.0.tar.gz |
660.7 KiB |
1.0 |
latest linux/jammy R-4.5 | quantreg.nonpar_1.0.tar.gz |
800.3 KiB |
1.0 |
latest linux/noble R-4.5 | quantreg.nonpar_1.0.tar.gz |
800.4 KiB |
1.0 |
latest source/ R- | quantreg.nonpar_1.0.tar.gz |
660.7 KiB |
1.0 |
2026-04-26 source/ R- | quantreg.nonpar_1.0.tar.gz |
660.7 KiB |
1.0 |
2026-04-23 source/ R- | quantreg.nonpar_1.0.tar.gz |
660.7 KiB |
1.0 |
2026-04-09 windows/windows R-4.5 | quantreg.nonpar_1.0.zip |
804.1 KiB |
1.0 |
2025-04-20 source/ R- | quantreg.nonpar_1.0.tar.gz |
660.7 KiB |