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 (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: 0.2
Depends: R (≥ 3.1)
Imports: ggplot2, pracma, mgcv, combinat, matrixStats, MASS, dplyr
Published: 2018-12-03
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

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Reference manual: lspartition.pdf
Package source: lspartition_0.2.tar.gz
Windows binaries: r-devel: lspartition_0.2.zip, r-release: lspartition_0.2.zip, r-oldrel: lspartition_0.2.zip
OS X binaries: r-release: lspartition_0.2.tgz, r-oldrel: lspartition_0.2.tgz
Old sources: lspartition archive

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