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Methodology for Analysis of Casualty Rate using Historical Combat Data
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전쟁사 자료를 이용한 인원손실률 분석 방법론

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Type
Academic journal
Author
Byung Joo Yoo (지상작전사령부)
Journal
Military Operations Research Society Of Korea Journal of the Military Operations Research Society of Korea (MORS-K) Vol.46 No.1 KCI Accredited Journals
Published
2020.6
Pages
31 - 42 (12page)

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Methodology for Analysis of Casualty Rate using Historical Combat Data
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Abstract· Keywords

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In order to establish a executable operations plan, it is necessary to predict accurately the resource requirements in wartime, and prepare a detailed operational sustainment plan including a mobilization plan or a wartime reinforcement plan. The reference data on the casualty rate is required for that, which can be estimated by using historical combat data. In this paper, a Poisson regression model is proposed using World War Ⅱ division-level combat data to analyze casualty rate for predicting the future. As an analysis methodology, a method of fitting a Quasi-poisson model and a negative binomial model as alternatives to resolve the error of underestimating the standard error are presented when over-dispersion occurs due to the characteristics of Poisson distribution. In particular, the Bayesian inference method is suggested to infer the posterior predictive distribution using the Markov chain Monte Carlo (NCMC) method and diversify the use of the analysis results.
#Poisson Regression Model #Casualty Rate #MCMC(Markov Chain Monte Carlo) #Bayesian Poisson Model #Negative Binomial Model

Contents

초록
Abstract
1. 서론
2. 이론적 배경과 기존 연구
3. 인원손실 분석 방법
4. 분석결과 활용과 미래 예측 방법
5. 결론
참고문헌

References (16)

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ROK Army / 2006 / FM 4-0-1 Technical and Logistics Specifications google schola Agresti, Alan / 2007 / An Introduction to Categorical Data Analysis / John Wiley & Sons, Inc. google schola Cameron, A. C. / 2013 / Regression analysis of count data(Vol. 53) / Cambridge university press google schola Chan, A. B. / 2009 / Bayesian poisson regression for crowd counting / 2009 IEEE 12th international conference on computer vision :545~551 google schola Chatterjee, S. / 2015 / Regression analysis by example / John Wiley & Sons google schola

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