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bayesQRsurvey (version 0.1.4)

Bayesian Quantile Regression Models for Complex Survey Data Analysis

Description

Provides Bayesian quantile regression models for complex survey data under informative sampling using survey-weighted estimators. Both single- and multiple-output models are supported. To accelerate computation, all algorithms are implemented in 'C++' using 'Rcpp', 'RcppArmadillo', and 'RcppEigen', and are called from 'R'. See Nascimento and Gonçalves (2024) and Nascimento and Gonçalves (2025, in press) .

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Install

install.packages('bayesQRsurvey')

Monthly Downloads

160

Version

0.1.4

License

MIT + file LICENSE

Issues

0

Pull Requests

0

Stars

0

Forks

1

Maintainer

Tomás Rodríguez Taborda

Last Published

October 22nd, 2025

Functions in bayesQRsurvey (0.1.4)

summary.bayesQRsurvey

Summary methods for bayesQRsurvey
prior

Create prior for Bayesian quantile regression models for complex survey data
print.bayesQRsurvey

Print methods for bayesQRsurvey model objects
plot.bqr.svy

Plot Method for Bayesian Weighted Quantile Regression
Anthro

Children anthropometric data
bqr.svy

Bayesian quantile regression for complex survey data
bayesQRsurvey-package

bayesQRsurvey: Bayesian Weighted Quantile Regression for complex survey designs with EM and MCMC Algorithm
mo.bqr.svy

Multiple-Output Bayesian quantile regression for complex survey data