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lspartition  

Nonparametric Estimation and Inference Procedures using Partitioning-Based Least Squares Regression
View on CRAN: Click here


Download and install lspartition package within the R console
Install from CRAN:
install.packages("lspartition")

Install from Github:
library("remotes")
install_github("cran/lspartition")

Install by package version:
library("remotes")
install_version("lspartition", "0.4")



Attach the package and use:
library("lspartition")
Maintained by
Yingjie Feng
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-04-19
Latest Update: 2019-08-08
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.
How to cite:
Yingjie Feng (2018). lspartition: Nonparametric Estimation and Inference Procedures using Partitioning-Based Least Squares Regression. R package version 0.4, https://cran.r-project.org/web/packages/lspartition
Previous versions and publish date:
0.1 (2018-04-19 09:55), 0.2 (2018-12-03 23:40), 0.3 (2019-06-04 23:10)
Other packages that cited lspartition R package
View lspartition citation profile
Other R packages that lspartition depends, imports, suggests or enhances
Functions, R codes and Examples using the lspartition R package
Some associated functions: lspartition-package . lspkselect . lsplincom . lsprobust . lsprobust.plot . 
Some associated R codes: lspartition-package.R . lspfunctions.R . lspkselect.R . lsplincom.R . lsprobust.R . lsprobust.plot.R .  Full lspartition package functions and examples
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