Tools for statistical analysis using partitioning-based least squares regression as described in Cattaneo, Farrell and Feng (2018) <arXiv:1804.04916>. lsprobust() for nonparametric point estimation of regression functions and derivatives thereof, and for robust bias-corrected (pointwise and uniform) inference procedures. lspkselect() for data-driven procedure for selecting 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: | 0.1 |
| Depends: | R (≥ 3.1) |
| Imports: | ggplot2, pracma, mgcv, combinat, matrixStats, MASS |
| Published: | 2018-04-19 |
| Author: | Matias D. Cattaneo, Max H. Farrell, Yingjie Feng |
| Maintainer: | Yingjie Feng <yjfeng at umich.edu> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | lspartition results |
| Reference manual: | lspartition.pdf |
| Package source: | lspartition_0.1.tar.gz |
| Windows binaries: | r-devel: lspartition_0.1.zip, r-release: lspartition_0.1.zip, r-oldrel: lspartition_0.1.zip |
| OS X binaries: | r-release: lspartition_0.1.tgz, r-oldrel: lspartition_0.1.tgz |
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