• Journal of Forest and Environmental Science
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• 제34권6호
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• pp.451-456
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• 2018

The use of single component distribution to describe the irregular stand structure of degraded forest often lead to bias. Such biasness can be overcome by the application of finite mixture distribution. Therefore, in this study, finite mixture distribution was used to characterise the irregular stand structure of the Gmelina arborea plantation in Omo forest reserve. Thirty plots, ten each from the three stands established in 1984, 1990 and 2005 were used. The data were pooled per stand and fitted. Four finite mixture distributions including normal mixture, lognormal mixture, gamma mixture and Weibull mixture were considered. The method of maximum likelihood was used to fit the finite mixture distributions to the data. Model assessment was based on negative loglikelihood value ($-{\Lambda}{\Lambda}$), Akaike information criterion (AIC), Bayesian information criterion (BIC) and root mean square error (RMSE). The results showed that the mixture distributions provide accurate and precise characterisation of the irregular diameter distribution of the degraded Gmelina arborea stands. The $-{\Lambda}{\Lambda}$, AIC, BIC and RMSE values ranged from -715.233 to -348.375, 703.926 to 1433.588, 718.598 to 1451.334 and 3.003 to 7.492, respectively. Their performances were relatively the same. This approach can be used to describe other irregular forest stand structures, especially the multi-species forest.

• 응용통계연구
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• 제31권1호
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• pp.109-122
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• 2018

임계값을 기준으로 그 보다 작은 값은 로그정규분포(lognormal distribution; LN)를, 큰 값은 일반화파레토분포(generalized Pareto distribution; GPD)를 따르는 합성 분포를 LN-GPD 합성분포라 한다. Scollnik (2007)은 LN-GPD 합성분포가 로그정규분포와 GPD를 합성 시킴으로써 자료의 손실 없이 꼬리가 두꺼운 분포에서 좋은 적합력을 가진다고 밝혔다. 본 논문에서는 시간에 따라 변하는 LN-GPD 평균모형을 다루었으며 방법론으로는 국소 다항최대우도법을 기반으로 추정하는 방법에 대해서 연구하였다. 시간에 따라 변하는 분포를 추정함으로써 자료에 대한 훨씬 자세한 이해가 가능하며 이는 곧 상담원 배치나 자원배분과 같은 운영관리에 큰 도움을 줄 수 있다. 본 연구는 GPD 분포만을 고려한 Beirlant와 Goegebeur (2004)를 확장하여 절삭한 로그정규분포를 추가하여 자료의 손실 없이 자료의 특징을 살펴볼 수 있다는데도 의의가 있다. 모의실험을 통해 제안한 방법론의 적절함을 살펴 보았고 실증 자료 분석으로 이스라엘 은행의 콜센터 서비스 시간에 대해 분석하여 상담원 배치와 관련된 흥미로운 결과를 찾을 수 있었다.

• Smart Structures and Systems
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• 제17권6호
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• pp.1087-1105
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• 2016

Traffic load and volume is one of the most important physical quantities for bridge safety evaluation and maintenance strategies formulation. This paper aims to conduct the statistical analysis of traffic volume information and the multimodal modeling of gross vehicle weight (GVW) based on the monitoring data obtained from the weigh-in-motion (WIM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. A genetic algorithm (GA)-based mixture parameter estimation approach is developed for derivation of the unknown mixture parameters in mixed distribution models. The statistical analysis of one-year WIM data is firstly performed according to the vehicle type, single axle weight, and GVW. The probability density function (PDF) and cumulative distribution function (CDF) of the GVW data of selected vehicle types are then formulated by use of three kinds of finite mixed distributions (normal, lognormal and Weibull). The mixture parameters are determined by use of the proposed GA-based method. The results indicate that the stochastic properties of the GVW data acquired from the field-instrumented WIM sensors are effectively characterized by the method of finite mixture distributions in conjunction with the proposed GA-based mixture parameter identification algorithm. Moreover, it is revealed that the Weibull mixture distribution is relatively superior in modeling of the WIM data on the basis of the calculated Akaike's information criterion (AIC) values.

• 경영과학
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• 제25권3호
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• pp.1-12
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• 2008

The Swaption is one of the popular Interest rates derivatives. In spite of such a popularity, the swaption pricing formula is hard to derived within the theoretical consistency. Most of swaption pricing model are heavily depending on the simulation technique. We present a new class of swaption model based on the multi-factor HJM levy-mixture model. A key contribution of this paper is to provide a generalized swaption pricing formula encompassing many market stylize facts. We provide an approximated closed form solution of the swaption price using the Gram-Charlier expansion. Specifically, the solution form is similar to the market models, since our approximation is based on the Lognormal distribution. It can be directly compared with the traditional Black's formula when the size of third and fourth moments are not so large. The proposed extended levy model is also expected to be capable of producing the volatility smiles and skewness.

• 한국통신학회논문지
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• 제19권8호
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• pp.1493-1502
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• 1994

본 논문에서는 순시 페이딩과 장구간 페이딩의 혼합인 Suzuki 페이딩 정확히 모사하는 새로운 광대역 채널 시뮬레이션 알고리즘을 제안한다. 제안된 알고리즘은 수신된 반사파들을 Suzuki 분포를 갖는 랜덤 신호로 발생시키며, Gaussian 분포로부터 대수정규 분포로의 변환을 이용함으로써 반사파들의 장구간 페이딩 성분들 사이의 상관 관계를 임의로 조정할 수 있다. 제안된 알고리즘은 시스템의 성능을 시뮬레이션하는 데 적용될 수 있다.

• Journal of Communications and Networks
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• 제18권2호
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• pp.182-189
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• 2016

The focus in this paper is on obtaining tight, simple algebraic-form bounds and invertible expressions for the average symbol error probability (ASEP) of M-ary phase shift keying (MPSK) in a class of composite fading channels. We employ the mixture gamma (MG) distribution to approximate the signal-to-noise ratio (SNR) distributions of fading models, which include Nakagami-m, Generalized-K ($K_G$), and Nakagami-lognormal fading as specific examples. Our approach involves using the tight upper and lower bounds that we recently derived on the Gaussian Q-function, which can easily be averaged over the general MG distribution. First, algebraic-form upper bounds are derived on the ASEP of MPSK for M > 2, based on the union upper bound on the symbol error probability (SEP) of MPSK in additive white Gaussian noise (AWGN) given by a single Gaussian Q-function. By comparison with the exact ASEP results obtained by numerical integration, we show that these upper bounds are extremely tight for all SNR values of practical interest. These bounds can be employed as accurate approximations that are invertible for high SNR. For the special case of binary phase shift keying (BPSK) (M = 2), where the exact SEP in the AWGN channel is given as one Gaussian Q-function, upper and lower bounds on the exact ASEP are obtained. The bounds can be made arbitrarily tight by adjusting the parameters in our Gaussian bounds. The average of the upper and lower bounds gives a very accurate approximation of the exact ASEP. Moreover, the arbitrarily accurate approximations for all three of the fading models we consider become invertible for reasonably high SNR.

• 응용통계연구
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• 제25권5호
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• pp.757-773
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• 2012

Traditional value at risk(S-VaR) has a difficulity in predicting the future risk of financial asset prices since S-VaR is a backward looking measure based on the historical data of the underlying asset prices. In order to resolve the deficiency of S-VaR, an economic value at risk(E-VaR) using the risk neutral probability distributions is suggested since E-VaR is a forward looking measure based on the option price data. In this study E-VaR is estimated by assuming the generalized gamma distribution(GGD) as risk neutral density function which is implied in the option. The estimated E-VaR with GGD was compared with E-VaR estimates under the Black-Scholes model, two-lognormal mixture distribution, generalized extreme value distribution and S-VaR estimates under the normal distribution and GARCH(1, 1) model, respectively. The option market data of the KOSPI 200 index are used in order to compare the performances of the above VaR estimates. The results of the empirical analysis show that GGD seems to have a tendency to estimate VaR conservatively; however, GGD is superior to other models in the overall sense.