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Detection of outliers in the unreplicated linear circular functional relationship model via functional form

机译:通过函数形式检测非复制线性圆函数关系模型中的异常值

摘要

In this paper we consider the problem of outliers for the functional relationship model of circular variables by transforming the circular data to continuous or real line data set via complex form. The COVRATIO statistic is extended from the linear regression models to the proposed model to detect any possible outliers. The cut-off points are obtained and the power of performance is examined by simulation studies. The model is illustrated with an application to the analysis of wind direction data recorded by two different techniques and the detection procedure of outliers is implied.
机译:在本文中,通过将循环数据通过复杂形式转换为连续或实线数据集,我们考虑了循环变量功能关系模型的离群值问题。 COVRATIO统计量已从线性回归模型扩展到建议的模型,以检测任何可能的异常值。获得了临界点,并通过仿真研究来检验性能的力量。将该模型应用于通过两种不同技术记录的风向数据分析中,并提出了离群值的检测方法。

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