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Qest
View on CRAN: Click
here
Download and install Qest package within the R console
Install from CRAN:
install.packages("Qest")
Install from Github:
library("remotes")
install_github("cran/Qest")
Install by package version:
library("remotes")
install_version("Qest", "1.0.1")
Attach the package and use:
library("Qest")
Maintained by
Gianluca Sottile
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-04-05
Latest Update: 2024-01-23
Description:
Quantile-based estimators (Q-estimators) can be used to fit any parametric distribution, using its quantile function. Q-estimators are usually more robust than standard maximum likelihood estimators. The method is described in: Sottile G. and Frumento P. (2022). Robust estimation and regression with parametric quantile functions. .
How to cite:
Gianluca Sottile (2022). Qest: Quantile-Based Estimator. R package version 1.0.1, https://cran.r-project.org/web/packages/Qest. Accessed 21 Dec. 2024.
Previous versions and publish date:
1.0.0 (2022-04-05 11:20)
Other packages that cited Qest R package
View Qest citation profile
Other R packages that Qest depends,
imports, suggests or enhances
Complete documentation for Qest
Functions, R codes and Examples using
the Qest R package
Some associated functions: Qcoxph.control . Qcoxph . Qest-package . Qest.control . Qlm.fit . Qlm . invQ . summary.Qest .
Some associated R codes: Qcoxph_covar_and_loss.R . Qcoxph_ee.R . Qest.R . Qest_S3methods.R . Qest_aux.R . Qest_covar_and_loss.R . Qest_ee.R . Qlm.R . Qlm_S3methods.R . Qlm_aux.R . Qlm_covar_and_loss.R . Qlm_ee.R . auxiliary.R . Full Qest package functions and examples
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