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robregcc  

Robust Regression with Compositional Covariates
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("robregcc", "1.1")



Attach the package and use:
library("robregcc")
Maintained by
Aditya Mishra
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-10-14
Latest Update: 2020-07-25
Description:
We implement the algorithm estimating the parameters of the robust regression model with compositional covariates. The model simultaneously treats outliers and provides reliable parameter estimates. Publication reference: Mishra, A., Mueller, C.,(2019) .
How to cite:
Aditya Mishra (2019). robregcc: Robust Regression with Compositional Covariates. R package version 1.1, https://cran.r-project.org/web/packages/robregcc. Accessed 03 Dec. 2024.
Previous versions and publish date:
1.0 (2019-10-14 17:40)
Other packages that cited robregcc R package
View robregcc citation profile
Other R packages that robregcc depends, imports, suggests or enhances
Complete documentation for robregcc
Functions, R codes and Examples using the robregcc R package
Some associated functions: classo . classo_path . coef_cc . cpsc_sp . plot_cv . plot_path . plot_resid . residuals . robregcc_option . robregcc_sim . robregcc_sp . simulate_robregcc . 
Some associated R codes: RcppExports.R . data.R . extract.R . misc.R . plots_robregcc.R . robregcc.R .  Full robregcc package functions and examples
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