Tools for statistical analysis using partitioning-based least squares regression as described in Cattaneo, Farrell and Feng (2019a, <arXiv:1804.04916>) and Cattaneo, Farrell and Feng (2019b, <arXiv:1906.00202>): lsprobust() for nonparametric point estimation of regression functions and their derivatives and for robust bias-corrected (pointwise and uniform) inference; lspkselect() for data-driven selection of the IMSE-optimal number of knots; lsprobust.plot() for regression plots with robust confidence intervals and confidence bands; lsplincom() for estimation and inference for linear combinations of regression functions from different groups.
| Version: | 0.4 |
| Depends: | R (≥ 3.1) |
| Imports: | ggplot2, pracma, mgcv, combinat, matrixStats, MASS, dplyr |
| Published: | 2019-08-08 |
| Author: | Matias D. Cattaneo, Max H. Farrell, Yingjie Feng |
| Maintainer: | Yingjie Feng <yingjief at princeton.edu> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | lspartition results |
| Reference manual: | lspartition.pdf |
| Package source: | lspartition_0.4.tar.gz |
| Windows binaries: | r-devel: lspartition_0.4.zip, r-release: lspartition_0.4.zip, r-oldrel: lspartition_0.4.zip |
| macOS binaries: | r-release: lspartition_0.4.tgz, r-oldrel: lspartition_0.4.tgz |
| Old sources: | lspartition archive |
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