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.

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Description file content

Package
lspartition
Type
Package
Title
Nonparametric Estimation and Inference Procedures using Partitioning-Based Least Squares Regression
Version
0.2
Date
2018-12-03
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 (2018) . 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.
Depends
R (>= 3.1)
License
GPL-2
Encoding
UTF-8
LazyData
true
Imports
ggplot2, pracma, mgcv, combinat, matrixStats, MASS, dplyr
RoxygenNote
6.0.1
NeedsCompilation
no
Packaged
2018-12-03 22:15:21 UTC; Yingjie
Repository
CRAN
Date/Publication
2018-12-03 22:40:03 UTC

install.packages('lspartition')

0.2

6 days ago

Yingjie Feng

GPL-2

Depends on

R (>= 3.1)

Imports

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

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