ScholarGate
Assistente

Comparar métodos

Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.

Regressão Bayesiana Quantil-sobre-Quantil×Regressão Quantílica×
ÁreaEconometriaEconometria
FamíliaRegression modelRegression model
Ano de origem2015–20191978
Autor originalBayesian QQ framework combines Sim & Zhou (2015) QQ regression with Bayesian quantile regression (Yu & Moyeed, 2001)Koenker & Bassett
TipoNonparametric quantile regression with Bayesian estimationConditional quantile regression
Fonte seminalSim, N., & Zhou, H. (2015). Oil prices, US stock return, and the dependence between their quantiles. Journal of Banking and Finance, 55, 1–8. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
Outros nomesBayesian QQR, Bayesian QQ regression, Bayes quantile-on-quantile, BQQ regressionconditional quantile regression, regression quantiles, Kantil Regresyon
Relacionados65
ResumoBayesian Quantile-on-Quantile (BQQ) Regression extends the Sim-Zhou quantile-on-quantile framework by replacing frequentist local linear estimation with Bayesian posterior inference. For each pair of quantiles (theta of the outcome, tau of the predictor), the method yields a full posterior distribution over the slope, enabling uncertainty quantification across the entire bivariate quantile surface — a key advantage when sample sizes are moderate and tail quantiles are sparse.Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails.
ScholarGateConjunto de dados
  1. v1
  2. 2 Fontes
  3. PUBLISHED
  1. v1
  2. 2 Fontes
  3. PUBLISHED

Ir para a pesquisa Baixar slides

ScholarGateComparar métodos: Bayesian Quantile-on-Quantile Regression · Quantile Regression. Recuperado em 2026-06-17 de https://scholargate.app/pt/compare