제약조건이 있는 베이지안 비모수 회귀모형을 활용한 방사선 반응자료 분석

국문 초록 (Abstract)

본 논문에서는 제약조건 (shape-restriction)이 있는 베이지안 비모수 회귀모형 (Bayesian non-parametric regression models)을 이용하여 방사선 반응자료 (radiation response data)를 분석한다. 특히, 식품에 방사선을 조사 (irradiation)하여 얻어진 반응 자료를 분석하고 베이지안 추론 (Bayesian inference)의 결과를 제시한다. 베이지안 추론을 위해 사후분포 (posterior distribution)는 가우시안 분포를 근사 분포로 하는 가수시안 변분 베이즈 (Gaussian variational Bayes) 근사 방법을 활용하여 근사하고, 해밀토니안 몬테카를로 (Hamiltonian Monte Carlo)에 기반한 마코프 체인 몬테 카를로 (Markov chain Monte Carlo)방법과의 비교를 통해 변분 추론 (variational inference)의 타당성을 제시한다.

다국어 초록 (Multilingual Abstract)

In this paper we analyze radiation response data using Bayesian nonparametric regression models with shape-restriction. Particularly, we present a Bayesian inference for analysis of radiation response data obtained by irradiating polymer material and food with radiation. For Bayesian inference, we approximate a posterior distribution using a Gaussian variational Bayes algorithm that uses Gaussian distributions as variational approximation distributions. We compare the variational approximation algorithm with a Markov chain Monte Carlo method that is based on Hamiltonian Monte Carlo and then present validity of variational inference.

목차 (Table of Contents)

• 요약
• 1. 서론
• 2. 방사선 반응자료
• 3. 베이지안 비모수 회귀모형
• 4. 방사선 반응 자료의 분석 결과
• 5. 결론
• References
• Abstract

참고문헌 (Reference)

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