lspartition: Nonparametric Estimation and Inference Procedures using Partitioning-Based Least Squares Regression

Tools for statistical analysis using partitioning-based least squares regression as described in Cattaneo, Farrell and Feng (2019a, <doi:10.48550/arXiv.1804.04916>) and Cattaneo, Farrell and Feng (2019b, <doi:10.48550/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
DOI: 10.32614/CRAN.package.lspartition
Author: Matias D. Cattaneo, Max H. Farrell, Yingjie Feng
Maintainer: Yingjie Feng <yingjief at>
License: GPL-2
NeedsCompilation: no
CRAN checks: lspartition results


Reference manual: lspartition.pdf


Package source: lspartition_0.4.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): lspartition_0.4.tgz, r-oldrel (arm64): lspartition_0.4.tgz, r-release (x86_64): lspartition_0.4.tgz, r-oldrel (x86_64): lspartition_0.4.tgz
Old sources: lspartition archive


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