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PLRModels  

Statistical Inference in Partial Linear Regression Models
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("PLRModels", "1.4")



Attach the package and use:
library("PLRModels")
Maintained by
Ana Lopez-Cheda
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2013-06-26
Latest Update: 2023-08-19
Description:
Contains statistical inference tools applied to Partial Linear Regression (PLR) models. Specifically, point estimation, confidence intervals estimation, bandwidth selection, goodness-of-fit tests and analysis of covariance are considered. Kernel-based methods, combined with ordinary least squares estimation, are used and time series errors are allowed. In addition, these techniques are also implemented for both parametric (linear) and nonparametric regression models.
How to cite:
Ana Lopez-Cheda (2013). PLRModels: Statistical Inference in Partial Linear Regression Models. R package version 1.4, https://cran.r-project.org/web/packages/PLRModels. Accessed 26 Oct. 2026.
Previous versions and publish date:
(2026-07-09 08:16), 1.0 (2013-06-26 18:08), 1.1 (2014-01-01 21:38), 1.2 (2022-07-14 12:40), 1.3 (2023-07-03 00:40)
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Complete documentation for PLRModels
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