• Communications for Statistical Applications and Methods
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• v.28 no.2
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• pp.99-118
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• 2021

In this paper, we introduce an extended form of the inverse power Lomax model via Marshall-Olkin approach. We call it the Marshall-Olkin inverse power Lomax (MOIPL) distribution. The four- parameter MOIPL distribution is very flexible which contains some former and new models. Vital properties of the MOIPL distribution are affirmed. Maximum likelihood estimators and approximate confidence intervals are considered under Type I censored samples. Maximum likelihood estimates are evaluated according to simulation study. Bayesian estimators as well as Bayesian credible intervals under symmetric loss function are obtained via Markov chain Monte Carlo (MCMC) approach. Finally, the flexibility of the new model is analyzed by means of two real data sets. It is found that the MOIPL model provides closer fits than some other models based on the selected criteria.

• Communications for Statistical Applications and Methods
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• v.3 no.3
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• pp.291-297
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• 1996

In this paper, we propose the jackknife estimator and the bootstrap estimator of Gini index of the two-parameter exponential distribution when the location parameter $\theta$ is unknown and the scale parameter $\sigma$is known. Sinilarly, we propose the bias location parameter $\theta$ and the scale parameter $\sigma$ are unknown. The bootstrap estimator is more efficient than the other estimators when the location parameter $\theta$is unknown and the scale parameter $\sigma$ is known, and the bias corrected estimator is more efficient than the MLE when both the location parameter $\theta$ and the scale parameter $\sigma$are unknown.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.19 no.2
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• pp.16-22
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• 2011

It is recognized that the control surface fault is detected by monitoring the value of the coefficients due to the control surface deviation. It is found out the control surface stuck position by comparing the trim value with the reference value. To detect and isolate the fault, two mixed methods apply to the real-time parameter estimation and similarity measure. If the scatter of aerodynamic coefficients for the fault and normal are closing nearly, fault decision is difficult. Applying similarity measure to decide for fault or not, it makes a clear and easy distinction between fault and normal. Low power processor is applied to the real-time parameter estimator and computation of similarity measure.

• Journal of information and communication convergence engineering
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• v.7 no.3
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• pp.392-398
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• 2009

A novel approach is presented to improve the array performance of the alternate mainbeam nulling in a linearly constrained adaptive array processor in coherent environment. The convergence parameters in the linearly constrained LMS algorithm with a unit gain constraint and a null constraint in the direction of the desired signal are adaptively estimated to reduce the error power between the desired signal and the array output in the 2-dimensional convergence parameter space. It is shown that the case for estimating the convergence parameter for the unit gain constraint with that for null constraint fixed performs best. Also, it is observed that the proposed method performs significantly better than conventional methods as the number of coherent interferences increases.

• Communications for Statistical Applications and Methods
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• v.16 no.6
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• pp.1055-1066
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• 2009

Many articles have considered a hybrid censoring scheme, which is a mixture of Type-I and Type-II censoring schemes. We introduce a double hybrid censoring scheme and derive some approximate maximum likelihood estimators(AMLEs) of the scale parameter for the half logistic distribution under the proposed double hybrid censored samples. The scale parameter is estimated by approximate maximum likelihood estimation method using two different Taylor series expansion types. We also obtain the maximum likelihood estimator(MLE) and the least square estimator(LSE) of the scale parameter under the proposed double hybrid censored samples. We compare the proposed estimators in the sense of the mean squared error. The simulation procedure is repeated 10,000 times for the sample size n = 20(10)40 and various censored samples. The performances of the AMLEs and MLE are very similar in all aspects but the MLE and LSE have not a closed-form expression, some numerical method must be employed.

• Journal of the Korean Data and Information Science Society
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• v.25 no.3
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• pp.633-641
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• 2014

The exponential distibution is one of the most popular distributions in analyzing the lifetime data. In this paper, we propose multiply Type I hybrid censoring. And this paper presents the statistical inference on the scale parameter for the exponential distribution when samples are multiply Type I hybrid censoring. The scale parameter is estimated by approximate maximum likelihood estimation methods using two different Taylor series expansion types ($AMLE_I$, $AMLE_{II}$). We also obtain the maximum likelihood estimator (MLE) of the scale parameter ${\sigma}$ under the proposed multiply Type I hybrid censored samples. We compare the estimators in the sense of the root mean square error (RMSE). The simulation procedure is repeated 10,000 times for the sample size n=20 and 40 and various censored schemes. The $AMLE_{II}$ is better than $AMLE_I$ in the sense of the RMSE.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1147-1155
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• 2018

This paper presents an improved method to determine the internal parameters for improving accuracy of a lithium ion battery equivalent circuit model. Conventional methods for the parameter estimation directly using the curve fitting results generate the phenomenon to be incorrect due to the influence of the internal capacitive impedance. To solve this phenomenon, simple correction procedure with transient state analysis is proposed and added to the parameter estimation method. Furthermore, conventional dynamic equation for correction is enhanced with advanced RC impedance dynamic equation so that the proposed modeling results describe the battery dynamic characteristics more exactly. The improved accuracy of the battery model by the proposed modeling method is verified by single cell experiments compared to the other type of models.

• Communications for Statistical Applications and Methods
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• v.17 no.6
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• pp.811-827
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• 2010

This paper deals with a density estimation method in binary choice models that can be regarded as a statistical inverse problem. We use an orthogonal basis to estimate density function and consider the choice of an appropriate truncation parameter to reflect the model complexity and the prediction accuracy. We propose a data-dependent rule to choose the truncation parameter in the context of binary choice models. A numerical simulation is provided to illustrate the performance of the proposed method.

• Journal of Biosystems Engineering
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• v.43 no.4
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• pp.410-419
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• 2018

Purpose: CLIMEX, a species distribution modeling tool, includes various types of parameters representing climatic conditions; the estimation of these parameters directly determines the model accuracy. In this study, we investigated the sensitivity of parameters for the climatic suitability calculated by CLIMEX for Metcalfa pruinosa in South Korea. Methods: We first changed 12 parameters and identified the three significant parameters that considerably affected the CLIMEX simulation response. Results: The result indicated that the simulation was highly sensitive to changes in lower optimal temperatures, lower soil moisture thresholds, and cold stress accumulation rate based on the sensitivity index, suggesting that these were the fundamental parameters to be used for fitting the simulation into the actual distribution. Conclusion: Sensitivity analysis is effective for estimating parameter values, and selecting the most important parameters for improving model accuracy.

• Journal of the Society of Naval Architects of Korea
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• v.40 no.5
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• pp.43-52
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• 2003

Two methods which estimate manoeuvring derivatives in the model of hydrodynamic force and moment acting on a manoeuvring ship using sea trial data were compared. One is the widely used parameter estimation method by using the Extended Kalman Filter (EKF), which estimates state variables of linearized state space model at every instant after dealing with the coefficients as the augmented state variables. The other one is the Estimation-Before-Modeling (EBM) technique, so called the two-step method. In the first step, hydrodynamic force of which dynamic model is assumed the third-order Gauss-Markov process is estimated along with motion variables by the EKF and the modified Bryson-Frazier smoother. Then, in the next step, manoeuvring derivatives are identified through the regression analysis. If the exact structure of hydrodynamic force could be known, which was an ideal case, the EKF method would be regarded as being more superior compared to the EBM technique. However the EBM technique was more robust than the EKF method from a realistic point of view where the assumed model structure was slightly different from the real one.