CAJ | 학술논문

函数型数据本质上是一种复杂数据，其抽样、生成、结构和关联程度都会影响到数据的复杂性和描述性，有些情形甚至连基本的可视化描述都成为难点。在利用函数型数据的主成分得分、图基的数据深度和密度概念的基础上，引入函数型数据的打包图和箱线图，并针对函数型数据的图形分析提出了函数型数据异常值检测的三种方法。与已有的检测方法相比较，所提三种方法更易于识别函数型数据的异常值。
함수형수거본질상시일충복잡수거，기추양、생성、결구화관련정도도회영향도수거적복잡성화묘술성，유사정형심지련기본적가시화묘술도성위난점。재이용함수형수거적주성분득분、도기적수거심도화밀도개념적기출상，인입함수형수거적타포도화상선도，병침대함수형수거적도형분석제출료함수형수거이상치검측적삼충방법。여이유적검측방법상비교，소제삼충방법경역우식별함수형수거적이상치。
As one kind of complex data essentially ,functional data can be affected in its complexity and descriptive nature by sampling ,producing ,structure and degree of association easily ,even basic visual descriptions of it has become difficult .In general ,the usual graphical -analytical method of functional data is the traditional method called data smoothing .Through this method ,status ,structures and trends of functional data can be described by the smooth curve .This paper introduces package diagram and box plot of functional data into the scores of principal component and the concept of data depth and density of Turkey . Simultaneously , while graphical analysis of functional data develops , tests of outliers in functional data have been resulted .Compared with the existing detection methods ,the proposed method by this paper is easier to identify the outliers of functional data .