Qest-package: Quantile-Based Estimator

In Qest: Quantile-Based Estimator

Quantile-Based Estimator

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. <doi:10.1016/j.csda.2022.107471>.

Details

Package:	Qest
Type:	Package
Version:	1.0.1
Date:	2024-01-22
License:	GPL-2

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Author(s)

Gianluca Sottile [aut, cre], Paolo Frumento [aut]

Maintainer: Gianluca Sottile <[e-mail]>

References

Sottile G, and Frumento P (2022). Robust estimation and regression with parametric quantile functions. Computational Statistics and Data Analysis. <doi:10.1016/j.csda.2022.107471>

See Also

Qest, Qlm, Qcoxph

Examples

## Not run: 
Qest(y ~ x, Q, start) # General-purpose Q-estimator
Qlm(y ~ x) # Q-estimation of linear models
Qcoxph(Surv(time, event) ~ x) # Q-estimation of proportional hazards models

## End(Not run)

Qest documentation built on May 29, 2024, 8:57 a.m.