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pqrfe
View on CRAN: Click
here
Download and install pqrfe package within the R console
Install from CRAN:
install.packages("pqrfe")
Install from Github:
library("remotes")
install_github("cran/pqrfe")
Install by package version:
library("remotes")
install_version("pqrfe", "1.1")
Attach the package and use:
library("pqrfe")
Maintained by
Ian Meneghel Danilevicz
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-10-20
Latest Update: 2022-12-01
Description:
Quantile regression with fixed effects is a general model for longitudinal data. Here we proposed to solve it by several methods. The estimation methods include three loss functions as check, asymmetric least square and asymmetric Huber functions; and three structures as simple regression, fixed effects and fixed effects with penalized intercepts by LASSO.
How to cite:
Ian Meneghel Danilevicz (2022). pqrfe: Penalized Quantile Regression with Fixed Effects. R package version 1.1, https://cran.r-project.org/web/packages/pqrfe. Accessed 22 Dec. 2024.
Previous versions and publish date:
1.0 (2022-10-20 09:02)
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imports, suggests or enhances
Complete documentation for pqrfe
Functions, R codes and Examples using
the pqrfe R package
Some associated functions: check_lambda . choice_p . clean_data . d_psi_als . d_psi_mq . f_den . f_tab . loss_er . loss_erfe . loss_erlasso . loss_mqr . loss_mqrfe . loss_mqrlasso . loss_qr . loss_qrfe . loss_qrlasso . mpqr . optim_er . optim_erfe . optim_erlasso . optim_mqr . optim_mqrfe . optim_mqrlasso . optim_qr . optim_qrfe . optim_qrlasso . plot_taus . pqr . pqrfe-package . print.PQR . psi_als . psi_mq . q_cov . rho_koenker . rho_mq . sgf .
Some associated R codes: PQRFE_main.R . RcppExports.R . Full pqrfe package functions and examples
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