• Title/Summary/Keyword: method of moments estimation

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On the Effects of Plotting Positions to the Probability Weighted Moments Method for the Generalized Logistic Distribution

  • Kim, Myung-Suk
    • Communications for Statistical Applications and Methods
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    • v.14 no.3
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    • pp.561-576
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    • 2007
  • Five plotting positions are applied to the computation of probability weighted moments (PWM) on the parameters of the generalized logistic distribution. Over a range of parameter values with some finite sample sizes, the effects of five plotting positions are investigated via Monte Carlo simulation studies. Our simulation results indicate that the Landwehr plotting position frequently tends to document smaller biases than others in the location and scale parameter estimations. On the other hand, the Weibull plotting position often tends to cause larger biases than others. The plotting position (i - 0.35)/n seems to report smaller root mean square errors (RMSE) than other plotting positions in the negative shape parameter estimation under small samples. In comparison to the maximum likelihood (ML) method under the small sample, the PWM do not seem to be better than the ML estimators in the location and scale parameter estimations documenting larger RMSE. However, the PWM outperform the ML estimators in the shape parameter estimation when its magnitude is near zero. Sensitivity of right tail quantile estimation regarding five plotting positions is also examined, but superiority or inferiority of any plotting position is not observed.

THE BIVARIATE F3-BETA DISTRIBUTION

  • Nadarajah Saralees
    • Communications of the Korean Mathematical Society
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    • v.21 no.2
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    • pp.363-374
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    • 2006
  • A new bivariate beta distribution based on the Appell function of the third kind is introduced. Various representations are derived for its product moments, marginal densities, marginal moments, conditional densities and conditional moments. The method of maximum likelihood is used to derive the associated estimation procedure as well as the Fisher information matrix.

New generalized inverse Weibull distribution for lifetime modeling

  • Khan, Muhammad Shuaib;King, Robert
    • Communications for Statistical Applications and Methods
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    • v.23 no.2
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    • pp.147-161
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    • 2016
  • This paper introduces the four parameter new generalized inverse Weibull distribution and investigates the potential usefulness of this model with application to reliability data from engineering studies. The new extended model has upside-down hazard rate function and provides an alternative to existing lifetime distributions. Various structural properties of the new distribution are derived that include explicit expressions for the moments, moment generating function, quantile function and the moments of order statistics. The estimation of model parameters are performed by the method of maximum likelihood and evaluate the performance of maximum likelihood estimation using simulation.

AN ERROR ESTIMATION FOR MOMENT CLOSURE APPROXIMATION OF CHEMICAL REACTION SYSTEMS

  • KIM, KYEONG-HUN;LEE, CHANG HYEONG
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • v.21 no.4
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    • pp.215-224
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    • 2017
  • The moment closure method is an approximation method to compute the moments for stochastic models of chemical reaction systems. In this paper, we develop an analytic estimation of errors generated from the approximation of an infinite system of differential equations into a finite system truncated by the moment closure method. As an example, we apply the result to an essential bimolecular reaction system, the dimerization model.

Comparison of parameter estimation methods for normal inverse Gaussian distribution

  • Yoon, Jeongyoen;Kim, Jiyeon;Song, Seongjoo
    • Communications for Statistical Applications and Methods
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    • v.27 no.1
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    • pp.97-108
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    • 2020
  • This paper compares several methods for estimating parameters of normal inverse Gaussian distribution. Ordinary maximum likelihood estimation and the method of moment estimation often do not work properly due to restrictions on parameters. We examine the performance of adjusted estimation methods along with the ordinary maximum likelihood estimation and the method of moment estimation by simulation and real data application. We also see the effect of the initial value in estimation methods. The simulation results show that the ordinary maximum likelihood estimator is significantly affected by the initial value; in addition, the adjusted estimators have smaller root mean square error than ordinary estimators as well as less impact on the initial value. With real datasets, we obtain similar results to what we see in simulation studies. Based on the results of simulation and real data application, we suggest using adjusted maximum likelihood estimates with adjusted method of moment estimates as initial values to estimate the parameters of normal inverse Gaussian distribution.

A data-adaptive maximum penalized likelihood estimation for the generalized extreme value distribution

  • Lee, Youngsaeng;Shin, Yonggwan;Park, Jeong-Soo
    • Communications for Statistical Applications and Methods
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    • v.24 no.5
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    • pp.493-505
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    • 2017
  • Maximum likelihood estimation (MLE) of the generalized extreme value distribution (GEVD) is known to sometimes over-estimate the positive value of the shape parameter for the small sample size. The maximum penalized likelihood estimation (MPLE) with Beta penalty function was proposed by some researchers to overcome this problem. But the determination of the hyperparameters (HP) in Beta penalty function is still an issue. This paper presents some data adaptive methods to select the HP of Beta penalty function in the MPLE framework. The idea is to let the data tell us what HP to use. For given data, the optimal HP is obtained from the minimum distance between the MLE and MPLE. A bootstrap-based method is also proposed. These methods are compared with existing approaches. The performance evaluation experiments for GEVD by Monte Carlo simulation show that the proposed methods work well for bias and mean squared error. The methods are applied to Blackstone river data and Korean heavy rainfall data to show better performance over MLE, the method of L-moments estimator, and existing MPLEs.

Stochastic Estimation of Phasor Voltage of Harmonics Using Multivariate Gram-Charlier Type A Series (다변수 그램-샬리어 급수 A형을 이용한 고조파 페이서 전압의 확률적 예측 계산)

  • Kim, Tae-Hyun;Park, In-Gyu;Park, Jong-Keun;Kang, Young-Shuk
    • Proceedings of the KIEE Conference
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    • 1987.11a
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    • pp.469-473
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    • 1987
  • This paper presents a method to estimate p.d.f.(probability density function) of harmonic phasor voltage. Because the quantity of harmonics is not fixed, stochastic analysis of harmonics is needed. Because it is impossible to obtain p.d.f. of voltage from p.d.f. of current directly, the moments of voltage and current are used. Firstly, the moments of current is calculated from p.d.f. of current. Secondly, the moments of voltage are calculated from the moments of current using the linearity of the moments. Finally, p.d.f. of voltage is estimated from the moments of voltage using Gram-Charlier Type A Series. [1] The moments of the p.d.f. obtained by the series and of the true p.d.f. is same up to given finite moments. Because current and voltage of harmonics are represented as not instantaneous values but phasors, the estimated value can be compared with the measured value and harmonic phasor voltage can be analyzed when the p.d.f. of phase is nonuniform as well as uniform.

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A numerical study of adjusted parameter estimation in normal inverse Gaussian distribution (Normal inverse Gaussian 분포에서 모수추정의 보정 방법 연구)

  • Yoon, Jeongyoen;Song, Seongjoo
    • The Korean Journal of Applied Statistics
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    • v.29 no.4
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    • pp.741-752
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    • 2016
  • Numerous studies have shown that normal inverse Gaussian (NIG) distribution adequately fits the empirical return distribution of financial securities. The estimation of parameters can also be done relatively easily, which makes the NIG distribution more useful in financial markets. The maximum likelihood estimation and the method of moments estimation are easy to implement; however, we may encounter a problem in practice when a relationship among the moments is violated. In this paper, we investigate this problem in the parameter estimation and try to find a simple solution through simulations. We examine the effect of our adjusted estimation method with real data: daily log returns of KOSPI, S&P500, FTSE and HANG SENG. We also checked the performance of our method by computing the value at risk of daily log return data. The results show that our method improves the stability of parameter estimation, while it retains a comparable performance in goodness-of-fit.

Estimation of Drought Rainfall by Regional Frequency Analysis Using L and LH-Moments (II) - On the method of LH-moments - (L 및 LH-모멘트법과 지역빈도분석에 의한 가뭄우량의 추정 (II)- LH-모멘트법을 중심으로 -)

  • Lee, Soon-Hyuk;Yoon , Seong-Soo;Maeng , Sung-Jin;Ryoo , Kyong-Sik;Joo , Ho-Kil;Park , Jin-Seon
    • Journal of The Korean Society of Agricultural Engineers
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    • v.46 no.5
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    • pp.27-39
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    • 2004
  • In the first part of this study, five homogeneous regions in view of topographical and geographically homogeneous aspects except Jeju and Ulreung islands in Korea were accomplished by K-means clustering method. A total of 57 rain gauges were used for the regional frequency analysis with minimum rainfall series for the consecutive durations. Generalized Extreme Value distribution was confirmed as an optimal one among applied distributions. Drought rainfalls following the return periods were estimated by at-site and regional frequency analysis using L-moments method. It was confirmed that the design drought rainfalls estimated by the regional frequency analysis were shown to be more appropriate than those by the at-site frequency analysis. In the second part of this study, LH-moment ratio diagram and the Kolmogorov-Smirnov test on the Gumbel (GUM), Generalized Extreme Value (GEV), Generalized Logistic (GLO) and Generalized Pareto (GPA) distributions were accomplished to get optimal probability distribution. Design drought rainfalls were estimated by both at-site and regional frequency analysis using LH-moments and GEV distribution, which was confirmed as an optimal one among applied distributions. Design rainfalls were estimated by at-site and regional frequency analysis using LH-moments, the observed and simulated data resulted from Monte Carlotechniques. Design drought rainfalls derived by regional frequency analysis using L1, L2, L3 and L4-moments (LH-moments) method have shown higher reliability than those of at-site frequency analysis in view of RRMSE (Relative Root-Mean-Square Error), RBIAS (Relative Bias) and RR (Relative Reduction) for the estimated design drought rainfalls. Relative efficiency were calculated for the judgment of relative merits and demerits for the design drought rainfalls derived by regional frequency analysis using L-moments and L1, L2, L3 and L4-moments applied in the first report and second report of this study, respectively. Consequently, design drought rainfalls derived by regional frequency analysis using L-moments were shown as more reliable than those using LH-moments. Finally, design drought rainfalls for the classified five homogeneous regions following the various consecutive durations were derived by regional frequency analysis using L-moments, which was confirmed as a more reliable method through this study. Maps for the design drought rainfalls for the classified five homogeneous regions following the various consecutive durations were accomplished by the method of inverse distance weight and Arc-View, which is one of GIS techniques.

Regional Drought Frequency Analysis of Monthly Precipitation with L-Moments Method in Nakdong River Basin (L-Moments법에 의한 낙동강유역 월강우량의 지역가뭄빈도해석)

  • 김성원
    • Journal of Environmental Science International
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    • v.8 no.4
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    • pp.431-441
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    • 1999
  • In this study, the regional frequency analysis is used to determine each subbasin drought frequency with reliable monthly precipitation and the L-Moments method which is almost unbiased and has very nearly a normal distribution is used for the parameter estimation of monthly precipitation time series in Nakdong river basin. As the result of this study, the duration of '93-'94 is most severe drought year than any other water year and the drought frequency is established as compared the regional frequency analysis result of cumulative precipitation of 12th duration months in each subbasin with that of 12th duration months in the major drought duration. The Linear regression equation is induced according to linear regression analysis of drought frequency between Nakdong total basin and each subbasin of the same drought duration. Therefore, as the foundation of this study, it can be applied proposed method and procedure of this study to the water budget analysis considering safety standards for the design of impounding facilities large-scale river basin and for this purpose, above all, it is considered that expansion of reliable preciptation data is needed in watershed rainfall station.

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