A Study on Two Sample Test for Interval-Valued Symbolic Data

• 발행기관: 한국자료분석학회
• 저자명: 이성건(Seong-Keon Lee)
• 간행물 정보: 『Journal of The Korean Data Analysis Society (JKDAS)』Vol.18 No.6, 2871~2878쪽, 전체 8쪽
• 주제분류: 자연과학 > 통계학
• 파일형태: PDF
• 발행일자: 2016.12.30

영문 초록

Symbolic data appear from various field of applications, such as social sciences, medical, industry and government experiment etc.. Symbolic data analysis treats new concepts that are underlying on the given raw data. It is important of the complex nature of big data. It can be multi-valued data, interval-valued data, histogram-valued data. Classical variables can be transformed into symbolic variables. So, we can reduce the size of the data. In this study, we consider statistical tests of two sample symbolic data, especially on interval-valued variables. It can be easily extended to other symbolic data such as histogram- valued variables. We are interested in two sample statistical tests for interval-valued variables. The first approach could be Kolmogorov-Smirnov (K-S) test for intervals. To construct K-S tests, we define empirical distributions of intervals and then compare proposed tests to classical ones. The p-value of the tests is calculated using permutation techniques with R. Blood pressure data is used as an applications to investigate their properties. We can find that the proposed method is competitive.

목차

1. Introduction

2. Empirical distribution and K-S test

3. K-S test for two sample interval-valued symbolic data

4. Application

5. Some concluding remarks

References

키워드

Symbolic data Interval-valued data Kolmogorov-Smirnov Test Permutations Big data