Binary quantile regression and variable selection: A new approach
DOI10.1080/07474938.2017.1417701zbMath1490.62414OpenAlexW2791350446MaRDI QIDQ5860953
Jian He, Katerina Aristodemou, Ke-ming Yu
Publication date: 4 March 2022
Published in: Econometric Reviews (Search for Journal in Brave)
Full work available at URL: http://bura.brunel.ac.uk/handle/2438/17162
quantile regressionvariable selectioniteratively reweighted least squaresbinary regressionadaptive Lassosmoothed maximum score estimatorwork trip mode choice
Applications of statistics to economics (62P20) Nonparametric regression and quantile regression (62G08) Ridge regression; shrinkage estimators (Lasso) (62J07)
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Cites Work
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- The Adaptive Lasso and Its Oracle Properties
- Asymmetric Least Squares Estimation and Testing
- Exact computation of max weighted score estimators
- Geoadditive expectile regression
- On confidence intervals for semiparametric expectile regression
- Cube root asymptotics
- Optimal expectile smoothing
- Semiparametric analysis of discrete response. Asymptotic properties of the maximum score estimator
- Censored regression quantiles
- Maximum score estimation of the stochastic utility model of choice
- Semiparametric estimation of a work-trip mode choice model
- Expectiles and \(M\)-quantiles are quantiles
- Quantile regression for longitudinal data
- Bayesian Lasso binary quantile regression
- Bayesian regularized quantile regression
- CONSISTENT AND CONSERVATIVE MODEL SELECTION WITH THE ADAPTIVE LASSO IN STATIONARY AND NONSTATIONARY AUTOREGRESSIONS
- The Bayesian Lasso
- M-quantiles
- Local Linear Quantile Regression
- A Smoothed Maximum Score Estimator for the Binary Response Model
- Regression Quantiles
- Asymmetric least squares regression estimation: A nonparametric approach∗
- Local NLLS estimation of semi‐parametric binary choice models
- On the Bootstrap of the Maximum Score Estimator
- Subsampling inference in cube root asymptotics with an application to Manski's maximum score estimator.
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