• Communications for Statistical Applications and Methods
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• 제26권5호
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• pp.473-495
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• 2019

In this paper, a new extension of Lindley distribution has been introduced. Certain characterizations based on truncated moments, hazard and reverse hazard function, conditional expectation of the proposed distribution are presented. Besides, these characterizations, other statistical/mathematical properties of the proposed model are also discussed. The estimation of the parameters is performed through different classical methods of estimation. Bayes estimation is computed under gamma informative prior under the squared error loss function. The performances of all estimation methods are studied via Monte Carlo simulations in mean square error sense. The potential of the proposed model is analyzed through two data sets. A modified goodness-of-fit test using the Nikulin-Rao-Robson statistic test is investigated via two examples and is observed that the new extension might be used as an alternative lifetime model.

• Communications for Statistical Applications and Methods
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• 제27권4호
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• pp.469-486
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• 2020

Entropy is an important term in statistical mechanics that was originally defined in the second law of thermodynamics. In this paper, we consider the maximum likelihood estimation (MLE), maximum product spacings estimation (MPSE) and Bayesian estimation of the entropy of an inverse Weibull distribution (InW) under a generalized type I progressive hybrid censoring scheme (GePH). The MLE and MPSE of the entropy cannot be obtained in closed form; therefore, we propose using the Newton-Raphson algorithm to solve it. Further, the Bayesian estimators for the entropy of InW based on squared error loss function (SqL), precautionary loss function (PrL), general entropy loss function (GeL) and linex loss function (LiL) are derived. In addition, we derive the Lindley's approximate method (LiA) of the Bayesian estimates. Monte Carlo simulations are conducted to compare the results among MLE, MPSE, and Bayesian estimators. A real data set based on the GePH is also analyzed for illustrative purposes.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2006년도 PROCEEDINGS OF JOINT CONFERENCEOF KDISS AND KDAS
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• pp.163-169
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• 2006

This paper deals with the comparison of parameter estimation methods in a 3-parameter Kappa distribution which is sometimes used in flood frequency analysis. The method of moment estimation(MME), L-moment estimation(L-ME), and maximum likelihood estimation(MLE) are applied to estimate three parameters. The performance of these methods are compared by Monte-carlo simulations. Especially for computing MME and L-ME, ike dimensional nonlinear equations are simplied to one dimensional equation which is calculated by the Newton-Raphson iteration under constraint. Based on the criterion of the mean squared error, the L-ME is recommended to use for small sample size $(n\leq100)$ while MLE is good for large sample size.

• Communications for Statistical Applications and Methods
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• 제3권2호
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• pp.37-42
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• 1996

Maximum likelihood estimation of Cholesky decomposition is considered under normality assumption. It is shown that maximum liklihood estimation gives a Cholesky decomposition of the sample covariance matrix. The joint distribution of the maximum likelihood estimators is derived. The ussual algorithm for a Cholesky decomposition is shown to be equivalent to a maximumlikelihood estimation of a Cholesky root when the underlying distribution is a multivariate normal one.

• Journal of Information Processing Systems
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• 제15권4호
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• pp.820-832
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• 2019

Estimation of accurate blood volume flow in ultrasound Doppler blood flow spectrograms is extremely important for clinical diagnostic purposes. Blood volume flow measurements require the assessment of both the velocity distribution and the cross-sectional area of the vessel. Unfortunately, the existing volume flow estimation algorithms by ultrasound lack the velocity space distribution information in cross-sections of a vessel and have the problems of low accuracy and poor stability. In this paper, a new robust ultrasound volume flow estimation method based on multigate (RMG) is proposed and the multigate technology provides detail information on the local velocity distribution. In this method, an accurate double iterative flow velocity estimation algorithm (DIV) is used to estimate the mean velocity and it has been tested on in vivo data from carotid. The results from experiments indicate a mean standard deviation of less than 6% in flow velocities when estimated for a range of SNR levels. The RMG method is validated in a custom-designed experimental setup, Doppler phantom and imitation blood flow control system. In vitro experimental results show that the mean error of the RMG algorithm is 4.81%. Low errors in blood volume flow estimation make the prospect of using the RMG algorithm for real-time blood volume flow estimation possible.

• Communications for Statistical Applications and Methods
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• 제24권3호
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• pp.227-240
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• 2017

In this paper, we introduce the inverted exponentiated Weibull (IEW) distribution which contains exponentiated inverted Weibull distribution, inverse Weibull (IW) distribution, and inverted exponentiated distribution as submodels. The proposed distribution is obtained by the inverse form of the exponentiated Weibull distribution. In particular, we explain that the proposed distribution can be interpreted by Marshall and Olkin's book (Lifetime Distributions: Structure of Non-parametric, Semiparametric, and Parametric Families, 2007, Springer) idea. We derive the cumulative distribution function and hazard function and calculate expression for its moment. The hazard function of the IEW distribution can be decreasing, increasing or bathtub-shaped. The maximum likelihood estimation (MLE) is obtained. Then we show the existence and uniqueness of MLE. We can also obtain the Bayesian estimation by using the Gibbs sampler with the Metropolis-Hastings algorithm. We also give applications with a simulated data set and two real data set to show the flexibility of the IEW distribution. Finally, conclusions are mentioned.

• 한국습지학회지
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• 제16권1호
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• pp.103-112
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• 2014

면적평균강우량의 산정은 가용 수자원의 정확한 양을 파악하고 강우-유출해석에 필수적인 입력자료이기 때문에 매우 중요하다. 이와 같은 면적평균강우량의 정확한 산정을 위한 필수적인 조건은 강우관측망의 균일한 공간적 분포이다. 본 연구에서는 보다 향상된 유역 면적평균강우량 산정을 위한 강우관측망의 공간분포 평가방법론을 제시하고, 이를 한강 및 금강 유역에 적용하였다. 강우관측소의 공간적 분포 특성은 최근린 지수(nearest neighbor index)를 이용하여 정량화하였다. 유역별 강우관측소의 공간적 분포가 면적평균강우량 산정에 미치는 영향을 평가하기 위하여 2013년의 강우사상에 대해 산술평균법, 티센가중법, 추정이론을 이용하여 면적평균강우량을 산정하고 각 경우에 대해 추정오차를 평가하였다. 그 결과 공간분포가 우수한 유역은 면적평균강우량의 추정오차가 상대적으로 작으며, 반대로 공간분포가 왜곡된 유역의 경우는 상대적으로 추정오차가 큼을 확인하였다.

• 응용통계연구
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• 제29권4호
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• pp.741-752
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• 2016

금융자산의 수익률 분포를 잘 설명할 수 있는 것으로 알려진 normal inverse Gaussian(NIG)분포는 모수의 조건에 의해 세 배의 초과첨도가 왜도 제곱의 5배보다 커야 하는데, 만약 관측된 초과첨도와 왜도의 관계가 이를 만족하지 못하거나 두 값이 매우 비슷하다면 모수를 안정적으로 추정하기 어렵게 된다. 이 논문에서 우리는 NIG분포의 모수추정에서 발생하는 이러한 문제점을 살펴보고 모의실험을 통해 이를 보정하는 방법을 찾아보았다. KOSPI, S&P500, FTSE와 HANG SENG의 실제 주가지수 자료에 적용하여 보정의 효과를 비교하고 VaR를 이용한 사후검증으로 보정된 추정방법의 성능을 평가해 보았다. 보정 방법을 이용하였을 때, 모수추정의 문제가 있던 구간을 포함한 모든 구간에서 안정적인 모수추정이 가능하였고 VaR를 통한 사후 검증에서도 분포의 성능이 떨어지지 않음을 확인하였다.

• 한국산림과학회지
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• 제59권1호
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• pp.46-50
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• 1983

Weibull 분포(分布)에 의(依)하여 임분(林分)의 직경분포(直徑分布)를 추정(推定)하여 그 적합성(適合性)을 Kolomogorov-Smirnov법(法)에 의하여 검정(檢定)한 결과(結果) 매우 잘 적합(適合)함을 나타내었다.

• International Journal of Reliability and Applications
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• 제3권1호
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• pp.51-60
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• 2002

This paper presents the methodology for obtaining point and interval estimating of the parameters of a new two-parameter distribution with multiple-censored and singly censored data (Type-I censoring or Type-II censoring) as well as complete data, using the maximum likelihood method. The basis is the likelihood expression for multiple-censored data. Furthermore, this model can be extended to a three-parameter distribution that is added a scale parameter. Then, the parameter estimation can be obtained by the graphical estimation on probability plot.