Journal of the Korean Data and Information Science Society

한국데이터정보과학회 (The Korean Data and Information Science Society)
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벌칙가능도함수를 이용한 1인가구와 저소득 독거노인의 공간군집 탐색

Investigating spatial clusters of single-person households and low-income elderly single-person using penalized likelihood

  • 투고 : 2017.10.11
  • 심사 : 2017.11.13
  • 발행 : 2017.11.30
⟨ 이전 논문 다음 논문 ⟩

초록

최근 1인 가구가 급격히 증가하고 있으며, 그 증가의 원인 중 하나는 독거노인 수의 증가이다. 이러한 거주형태 변화는 필연적으로 정책적인 변화를 요구하므로 1인 가구의 공간적인 분포를 파악하는 것은 중요한 문제로 볼 수 있다. 또한 공간적인 군집이 나타나게 된 요인들에 대해 이해하는 것은 효율적인 정책 수립에 유리 할 것이다. 본 연구에서는 사회경제적인 불평등을 반영하는 박탈지수 (deprivation index)를 설명변수로 고려하면서 1인 가구와 저소득 독거노인에 대한 공간 군집 탐색을 하였다. 이를 위해서 fused lasso를 이용한 공간 군집 탐색방법이 사용되었다. 이 방법을 통하여 낮은 사회경제적 수준이 l인가구와 저소득 독거노인의 수에 얼마나 영향을 미치는지 확인하고, 박탈정도의 효과가 보정된 공간군집을 살펴보았다. 또한 정수형 자료에서 벌칙가능도함수를 이용한 공간 군집 탐색을 할 수 있도록 구현된 R패키지의 사용법을 자세히 소개하였다.

Single-person households recently have been rapidly increasing and one reason may be the increment in elderly single-person. Since the change of living patterns is relevant to the government policy direction, it is important to understand how single-person households are clustered and which factors have influence on them. In this study, we tried to detect spatial clusters of single-person households and low-income elderly single-person households after adjusting for deprivation index. A recently developed fused lasso for Poisson data was used for data analysis and we provided the details on how to use it in R. From these analysis results, we observed the effect of socioeconomic level on the clusters and explained the reason why spatial clusters are shown after adjusting for deprivation index.

키워드

참고문헌

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