A convergent algorithm for quantile regression with smoothing splines
From MaRDI portal
Publication:672955
DOI10.1016/0167-9473(94)00018-EzbMath0875.62148WikidataQ127807283 ScholiaQ127807283MaRDI QIDQ672955
Yinyu Ye, Ronald J. Bosch, George G. Woodworth
Publication date: 28 February 1997
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Related Items
Quantiles, expectiles and splines, Simultaneous fitting of Bayesian penalised quantile splines, Constrained smoothing \(B\)-splines for the term structure of interest rates, Bayesian nonparametric quantile regression using splines, Multiple smoothing parameters selection in additive regression quantiles, Computing confidence intervals from massive data via penalized quantile smoothing splines, Imposing no-arbitrage conditions in implied volatilities using constrained smoothing splines
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Regression quantiles and trimmed least squares estimator in the nonlinear regression model
- Kernel and nearest-neighbor estimation of a conditional quantile
- Asymptotics for M-type smoothing splines
- Asymptotic properties of kernel estimators based on local medians
- Non-parametric estimation of conditional quantiles
- An \(O(\sqrt n L)\) iteration potential reduction algorithm for linear complementarity problems
- Consistent nonparametric regression. Discussion
- Nonparametric regression M-quantiles
- \(M\)-type smoothing splines with auxiliary scale estimation
- A Centered Projective Algorithm for Linear Programming
- Splines in Statistics
- Binary Regression Using an Extended Beta-Binomial Distribution, With Discussion of Correlation Induced by Covariate Measurement Errors
- On Computing Robust Splines and Applications