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, <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

Documentation:

Reference manual:

lspartition.pdf

Downloads:

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 (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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