The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Testing for Overdispersion in a Bivariate Negative Binomial Distribution Using Bootstrap Method

이변량 음이항 모형에서 붓스트랩 방법을 이용한 과대산포에 대한 검정

  • 전명식 (고려대학교 통계학과) ;
  • 정병철 (서울시립대학교 통계학과)
  • Published : 2008.04.30
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Abstract

The bootstrap method for the score test statistic is proposed in a bivariate negative binomial distribution. The Monte Carlo study shows that the score test for testing overdispersion underestimates the nominal significance level, while the score test for "intrinsic correlation" overestimates the nominal one. To overcome this problem, we propose a bootstrap method for the score test. We find that bootstrap methods keep the significance level close to the nominal significance level for testing the hypothesis. An empirical example is provided to illustrate the results.

본 연구에서는 이변량 음이항 분포에서 과대산포와 "내재적 상"의 존재유무에 대한 가설검정 문제를 다루었다. 과대산포에 대한 스코어 검정의 표준정규분포 근사는 명목 유의수준을 과소추정한 반면 "내재적 상"에 대한 스코어 검정은 명목유의수준을 과대 추정하고 있음을 보였다. 본 연구에서는 이와 같은 스코어 검정의 표준정규분포 근사의 문제점을 해결하기 위하여 붓스트랩 방법을 제안하였다. 스코어 검정에 대한 붓스트랩 방법은 두 검정에서 명목유의수준을 제대로 유지하고 검정력도 높게 나타나 스코어 검정의 표준정규분포 근사에 존재하는 문제를 해결하는 효율적인 대안으로 판단된다.

Keywords

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