Korean Journal of Environmental Biology (환경생물)

Korean Society of Environmental Biology (한국환경생물학회)
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A Review of Time Series Analysis for Environmental and Ecological Data

환경생태 자료 분석을 위한 시계열 분석 방법 연구

  • Mo, Hyoung-ho (Institute of Life Science and Natural Resources, Korea University) ;
  • Cho, Kijong (Division of Environmental Science and Ecological Engineering, Korea University) ;
  • Shin, Key-Il (Department of Statistics, Hankuk University of Foreign Studies)
  • 모형호 (고려대학교 생명자원연구소) ;
  • 조기종 (고려대학교 환경생태공학부) ;
  • 신기일 (한국외국어대학교 통계학과)
  • Received : 2016.12.21
  • Accepted : 2016.12.26
  • Published : 2016.12.31
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Abstract

Much of the data used in the analysis of environmental ecological data is being obtained over time. If the number of time points is small, the data will not be given enough information, so repeated measurements or multiple survey points data should be used to perform a comprehensive analysis. The method used for that case is longitudinal data analysis or mixed model analysis. However, if the amount of information is sufficient due to the large number of time points, repetitive data are not needed and these data are analyzed using time series analysis technique. In particular, with a large number of data points in the current situation, when we want to predict how each variable affects each other, or what trends will be expected in the future, we should analyze the data using time series analysis techniques. In this study, we introduce univariate time series analysis, intervention time series model, transfer function model, and multivariate time series model and review research papers studied in Korea. We also introduce an error correction model, which can be used to analyze environmental ecological data.

환경생태 자료 분석에 사용된 많은 자료가 시간에 따라 얻어지고 있다. 조사된 시점의 수가 적은 경우에는 자료가 충분한 정보를 주지 않기 때문에 반복 측정하거나 여러 지점을 조사하여 종합적인 분석을 수행하게 된다. 이때 사용하는 방법이 경시적 자료 분석(longitudinal data analysis) 또는 혼합모형(mixed model) 분석이다. 그러나 시점의 수가 많아 정보의 양이 충분하다면 반복적인 자료가 필요하지 않으며 이러한 자료는 시계열 분석 기법을 이용하여 분석하게 된다. 특히 현재와 같이 다수의 시점에서 얻어진 자료의 수가 많아지고 있는 상항에서 각 변수 간에 서로 어떤 영향을 주는지 또는 향후 어떤 경향을 띠게 되는지 예측을 원한다면 시계열 분석 기법을 사용하여 자료를 분석해야 한다. 본 연구에서는 단변량 시계열 분석(univariate time series analysis), 개입 분석(intervention time series model), 전이함수 모형 분석(transfer function model), 다변량 시계열 분석(multivariate time series model) 기법을 소개하고 현재까지 진행된 국내외 연구 논문을 살펴보았다. 또한 향후 환경생태 자료 분석에서 중요하게 사용될 수 있는 오차수정 모형(error correction model)을 소개하였다.

Keywords

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