Abstract
Application of quantile regression models with measurement errors in predictors is becoming increasingly popular. High leverage points in predictors can have substantial impacts on these models. Here, we propose a predictive leverage statistic for these models, assuming that the measurement errors follow a multivariate normal distribution, and derive its exact distribution. We compare its performance versus known predictive leverage statistics using simulation and a real dataset. The proposed statistic is shown to have desirable features. It is also the first predictive leverage statistic having its distribution derived in a closed form.
Original language | English |
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Pages (from-to) | 1-14 |
Number of pages | 14 |
Journal | Communications in Statistics: Simulation and Computation |
Early online date | 28 Jul 2016 |
DOIs | |
Publication status | Published - 2016 |
Keywords
- Elemental predictive leverage
- Elemental regression
- Elemental regression weight
- Elemental set
- Multiple case
- Quantile regression