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摘要翻译：
R包Quantreg.nonpar实现了非参数分位数回归方法，对部分线性分位数模型进行估计和推断。Quantreg.Nonpar通过对模型非参数部分的级数逼近，得到条件分位数函数及其导数的点估计。它还使用分析和重采样方法为相同函数提供协变量值和/或分位数指数区域上的逐点一致置信区间。本文是对包的介绍，并显示了包中包含的函数的基本功能。
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英文标题：
《quantreg.nonpar: An R Package for Performing Nonparametric Series
Quantile Regression》
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作者：
Michael Lipsitz, Alexandre Belloni, Victor Chernozhukov, and Iv\'an
Fern\'andez-Val
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最新提交年份：
2016
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分类信息：
一级分类：Statistics 统计学
二级分类：Computation 计算
分类描述：Algorithms, Simulation, Visualization
算法、模拟、可视化
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一级分类：Economics 经济学
二级分类：Econometrics 计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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英文摘要：
The R package quantreg.nonpar implements nonparametric quantile regression methods to estimate and make inference on partially linear quantile models. quantreg.nonpar obtains point estimates of the conditional quantile function and its derivatives based on series approximations to the nonparametric part of the model. It also provides pointwise and uniform confidence intervals over a region of covariate values and/or quantile indices for the same functions using analytical and resampling methods. This paper serves as an introduction to the package and displays basic functionality of the functions contained within.
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PDF链接：
https://arxiv.org/pdf/1610.08329
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