Modelling Flow in Gas Transmission Networks Using Shape-Constrained Expectile Regression
From MaRDI portal
Publication:5871000
DOI10.1007/978-3-030-73249-3_14OpenAlexW3181779297MaRDI QIDQ5871000
Thomas Kneib, Fabian Otto-Sobotka, Benjamin Hofner, Radoslava Mirkov
Publication date: 24 January 2023
Published in: Advances in Contemporary Statistics and Econometrics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/978-3-030-73249-3_14
Related Items
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Model-based boosting in R: a hands-on tutorial using the R package mboost
- Asymmetric Least Squares Estimation and Testing
- Geoadditive expectile regression
- Boosting algorithms: regularization, prediction and model fitting
- On confidence intervals for semiparametric expectile regression
- Boosting additive models using component-wise P-splines
- Optimal expectile smoothing
- Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
- Geoadditive Models
- NonparametricM-quantile regression using penalised splines
- Variable Selection and Model Choice in Geoadditive Regression Models
- Regression Quantiles
- Soap Film Smoothing
- Expectile and quantile regression—David and Goliath?
- Modelling and Forecasting Gas Flow on Exits of Gas Transmission Networks
- Generalized Additive Models for Location, Scale and Shape