ScholarGate
アシスタント

手法を比較

選択した手法を並べて確認できます。異なる行はハイライト表示されます。

ベイズ頑健回帰×分位点回帰×
分野統計学計量経済学
系統Regression modelRegression model
提唱年19931978
提唱者Geweke (1993); Gelman et al. (2013)Koenker & Bassett
種類Bayesian regression with heavy-tailed errorsConditional quantile regression
原典Geweke, J. (1993). Bayesian treatment of the independent Student-t linear model. Journal of Applied Econometrics, 8(S1), S19–S40. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
別名Bayesian heavy-tailed regression, Bayesian Student-t regression, robust Bayesian linear model, BRRconditional quantile regression, regression quantiles, Kantil Regresyon
関連65
概要Bayesian Robust Regression replaces the Gaussian error assumption of ordinary linear regression with a heavy-tailed distribution — most commonly the Student-t — and estimates all parameters in a Bayesian framework. The heavier tails give outliers less influence on the fitted line, yielding stable coefficient estimates and honest uncertainty intervals even when the data contain unusual observations.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.
ScholarGateデータセット
  1. v1
  2. 2 出典
  3. PUBLISHED
  1. v1
  2. 2 出典
  3. PUBLISHED

検索へ スライドをダウンロード

ScholarGate手法を比較: Bayesian Robust Regression · Quantile Regression. 2026-06-15に以下より取得 https://scholargate.app/ja/compare