지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록· 키워드
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The maximum entropy (maxent) approach provides an attractive and appealing method for obtaining a probability distribution in some limited information environments. The maxent approach, however, is not easy to use for practical application since analytic derivation of a maxent density is usually not feasible. This paper proposes a method of estimating and simulating an maxent density. It is a numerically tractable and stable method that is relatively simple in real computation. The proposed method is capable of handling problems for which existing methods are difficult to apply or are subject to occasional failure.
Monte Carlo results confirm that the proposed method can be well applied for cases when existing methods are subject to occasional failure.
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참고문헌 (15)
참고문헌 신청
Andersen, P. K. / 1982 / Cox’s regression model for counting processes: A large sample study / Annals of Statistics 10 : 1100 ~ 1120
Bera, A. K. / 2004 / Maximum entropy autoregressive conditionial heteroskedasticity model
Buchen, P. / 1996 / The maximum entropy distribution of an asset inferred from option prices / Journal of Financial and Quantitative Analysis 31 : 143 ~ 159
Golan, A. / 1996 / Maximum Entropy Econometrics: Robust Estimation with Limited Data / John Wiley and Sons
Jaynes, E. T. / 1957 / Information theory and statistical mechanics / Physics Review 106 : 620 ~ 630
Bera, A. K. / 2004 / Maximum entropy autoregressive conditionial heteroskedasticity model
Buchen, P. / 1996 / The maximum entropy distribution of an asset inferred from option prices / Journal of Financial and Quantitative Analysis 31 : 143 ~ 159
Golan, A. / 1996 / Maximum Entropy Econometrics: Robust Estimation with Limited Data / John Wiley and Sons
Jaynes, E. T. / 1957 / Information theory and statistical mechanics / Physics Review 106 : 620 ~ 630
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