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quokar: Quantile Regression Outlier Diagnostics with K Left Out Analysis
Diagnostics methods for quantile regression models for detecting influential observations: robust distance methods for general quantile regression models; generalized Cook's distance and Q-function distance method for quantile regression models using aymmetric Laplace distribution. Reference of this method can be found in Luis E. Benites, Víctor H. Lachos, Filidor E. Vilca (2015) <arXiv:1509.05099v1>; mean posterior probability and Kullback–Leibler divergence methods for Bayes quantile regression model. Reference of this method is Bruno Santos, Heleno Bolfarine (2016) <arXiv:1601.07344v1>.
Browse package contents
Package details |
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| Author | Wenjing Wang <wenjingwangr@gmail.com>, Di Cook <visnut@gmail.com>, Earo Wang <earo.wang@gmail.com> |
| Maintainer | Wenjing Wang <wenjingwangr@gmail.com> |
| License | GPL (>= 2) |
| Version | 0.1.0 |
| URL | https://github.com/wenjingwang/quokar |
| Package repository | View on CRAN |
| Installation |
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