본 논문은 완전히 잘못된 데이터가 포함된 회귀(regression) 문제에 사용되는 가우스-균일 혼합확률분포의 두 개의 매개변수 추정에 관하여 고찰한다. 논문에서는 기대값 최대화(Expectation Maximization)와 최우도추정(Maximum Likelihood Estimation)을 이용한 매개변수 추정 방법을 비교한다. 두 기법은 최적화 문제로 기술할 수 있고, 논문에서는 두 기법에서 사용하는 매개변수에 대한 적합도 척도의 개형을 도시하고 비교한다. 몬테-카를로(Monte Carlo) 접근을 통한 두 기법이 추정한 매개변수의 분포를 살펴본다.
KSP Keywords
Monte carlo, expectation maximization, maximum likelihood estimation(MLE)
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