Goodness of Fit and Related Inference Processes for Quantile Regression
Goodness of Fit and Related Inference Processes for Quantile Regression
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DOI：
10.1080/01621459.1999.10473882
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发表时间：
1999-02
影响因子：
3.7
通讯作者：
R. Koenker;J. Machado
中科院分区：
文献类型：
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作者：
R. Koenker;J. Machado
摘要本文介绍了一种类似于传统最小二乘回归的R2统计量的分位数回归的拟合优度过程。还制定了几个相关的推理过程，用于测试关于几个协变量在整个条件分位数函数范围内的联合效应的复合假设。推理过程的渐近行为被证明与早期涉及贝塞尔过程的p样本拟合优度理论密切相关。本文用一些假设的例子、对最近国际经济增长经验模型的应用以及一些蒙特卡洛证据来说明这种方法。
Abstract We introduce a goodness-of-fit process for quantile regression analogous to the conventional R2 statistic of least squares regression. Several related inference processes designed to test composite hypotheses about the combined effect of several covariates over an entire range of conditional quantile functions are also formulated. The asymptotic behavior of the inference processes is shown to be closely related to earlier p-sample goodness-of-fit theory involving Bessel processes. The approach is illustrated with some hypothetical examples, an application to recent empirical models of international economic growth, and some Monte Carlo evidence.