摘要翻译：
经济数据通常是由发生在连续时间的随机过程产生的，尽管观测可能只发生在离散时间。例如，电力和燃气的消耗是在连续的时间内发生的。由连续时间随机过程产生的数据称为函数数据。本文讨论了生成函数数据的两个或两个以上随机过程的比较问题。这些数据可能是通过一个随机实验产生的，在这个实验中有多种治疗方法。本文提出了一种检验同一随机过程产生所有函数数据假设的方法。这里描述的测试既适用于功能数据，也适用于多种治疗。它被实现为两个置换测试的组合。这保证了在有限样本中，每个检验拒绝一个正确的零假设的真实概率和名义概率是相等的。本文给出了在交替假设下检验的渐近幂的上下界。Monte Carlo实验的结果和天然气计费定价实验的应用表明了该方法的有效性。
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英文标题：
《Permutation Tests for Equality of Distributions of Functional Data》
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作者：
Federico A. Bugni, Joel L. Horowitz
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最新提交年份：
2021
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分类信息：

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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一级分类：Statistics        统计学
二级分类：Methodology        方法论
分类描述：Design, Surveys, Model Selection, Multiple Testing, Multivariate Methods, Signal and Image Processing, Time Series, Smoothing, Spatial Statistics, Survival Analysis, Nonparametric and Semiparametric Methods
设计，调查，模型选择，多重检验，多元方法，信号和图像处理，时间序列，平滑，空间统计，生存分析，非参数和半参数方法
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英文摘要：
  Economic data are often generated by stochastic processes that take place in continuous time, though observations may occur only at discrete times. For example, electricity and gas consumption take place in continuous time. Data generated by a continuous time stochastic process are called functional data. This paper is concerned with comparing two or more stochastic processes that generate functional data. The data may be produced by a randomized experiment in which there are multiple treatments. The paper presents a method for testing the hypothesis that the same stochastic process generates all the functional data. The test described here applies to both functional data and multiple treatments. It is implemented as a combination of two permutation tests. This ensures that in finite samples, the true and nominal probabilities that each test rejects a correct null hypothesis are equal. The paper presents upper and lower bounds on the asymptotic power of the test under alternative hypotheses. The results of Monte Carlo experiments and an application to an experiment on billing and pricing of natural gas illustrate the usefulness of the test.
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PDF链接：
https://arxiv.org/pdf/1803.00798