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.

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Description file content

Package
lspartition
Type
Package
Title
Nonparametric Estimation and Inference Procedures using Partitioning-Based Least Squares Regression
Version
0.4
Date
2019-08-08
Author
Matias D. Cattaneo, Max H. Farrell, Yingjie Feng
Maintainer
Yingjie Feng
Description
Tools for statistical analysis using partitioning-based least squares regression as described in Cattaneo, Farrell and Feng (2019a, ) and Cattaneo, Farrell and Feng (2019b, ): 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.
Depends
R (>= 3.1)
License
GPL-2
Encoding
UTF-8
LazyData
true
Imports
ggplot2, pracma, mgcv, combinat, matrixStats, MASS, dplyr
RoxygenNote
6.1.1
NeedsCompilation
no
Packaged
2019-08-08 20:21:51 UTC; Administrator
Repository
CRAN
Date/Publication
2019-08-08 22:40:06 UTC

install.packages('lspartition')

0.4

4 months ago

Yingjie Feng

GPL-2

Depends on

R (>= 3.1)

Imports

ggplot2, pracma, mgcv, combinat, matrixStats, MASS, dplyr

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