• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.889-898
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• 2002

In decision theoretic estimation, the loss function usually emphasizes precision of estimation. However, one may have interest in goodness of fit of the overall model as well as precision of estimation. From this viewpoint, Zellner(1994) proposed the balanced loss function which takes account of both "goodness of fit" and "precision of estimation". This paper considers estimation of the parameter of a Bernoulli distribution using Zellner's(1994) balanced loss function. It is shown that the sample mean $\overline{X}$, is admissible. More general results, concerning the admissibility of estimators of the form $a\overline{X}+b$ are also presented. Finally, minimax estimators and some numerical results are given at the end of paper,at the end of paper.

• Journal of the Korean Data and Information Science Society
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• v.11 no.1
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• pp.1-18
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• 2000

In this paper, we study several parameter estimation methods used for autoregressive processes and compare them in view of forecasting. The least square estimation, least absolute deviation estimation, robust estimation are compared through Monte Carlo simulations.

• Korean Journal of Construction Engineering and Management
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• v.9 no.6
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• pp.175-184
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• 2008

For deciding the profitability and feasibility of the construction project, the schematic estimation has to not only link the design decision-making but also estimate the cost with reliability. The prototype-based schematic estimation system was developed for easily linking with design-making and supports to evaluate the design alternatives in the design development stage but didn't consider the cost estimated by parameter and additional work items by users. This research presents the object-parameter based schematic estimation model in the design development stage that can lead to accurately estimate the cost by using historical data from the high-storied office buildings. For the development of the proposed model for schematic estimation, after analyzing and classifying the work items from the Bills of Quantities(BOQs) and drawings of historical data, this research proposed the methods of estimating cost in accordance with attributes of each work item. In addition, a case study is performed for the effectiveness as comparing the previous estimating method with the proposed model.

• Journal of international Conference on Electrical Machines and Systems
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• v.2 no.2
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• pp.184-189
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• 2013

This paper proposes a method for improving the performance of a position sensorless control system for a slotless surface permanent magnet synchronous motor (SPMSM) in a very low-speed region. In position sensorless control based on a motor model, accurate motor parameters are required because parameter errors would affect position estimation accuracy. Therefore, online parameter identification is applied in the proposed system. The error between the reference voltage and the voltage applied to the motor is also affect position estimation accuracy and stability, thus it is compensated to ensure accuracy and stability of the sensorless control system. In this study, two voltage error compensation methods are used, and the effects of the compensation methods are discussed. The performance of the proposed sensorless control method is evaluated by experimental results.

• Communications for Statistical Applications and Methods
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• v.27 no.1
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• pp.47-64
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• 2020

In this paper, we derive some estimators of the scale parameter of the exponentiated half-logistic distribution based on the multiply Type-I hybrid censoring scheme. We assume that the shape parameter λ is known. We obtain the maximum likelihood estimator of the scale parameter σ. The scale parameter is estimated by approximating the given likelihood function using two different Taylor series expansions since the likelihood equation is not explicitly solved. We also obtain Bayes estimators using prior distribution. To obtain the Bayes estimators, we use the squared error loss function and general entropy loss function (shape parameter q = -0.5, 1.0). We also derive interval estimation such as the asymptotic confidence interval, the credible interval, and the highest posterior density interval. Finally, we compare the proposed estimators in the sense of the mean squared error through Monte Carlo simulation. The average length of 95% intervals and the corresponding coverage probability are also obtained.

• International Journal of Reliability and Applications
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• v.18 no.2
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• pp.83-98
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• 2017

Stress-strength reliability problems arise frequently in applied statistics and related fields. In the context of reliability, the stress-strength model describes the life of a component, which has a random strength X and is subjected to random stress Y. The component fails at the instant that the stress applied to it exceeds the strength and the component will function satisfactorily whenever X > Y. The problem of estimation the reliability parameter in a stress-strength model R = P[Y < X], when X and Y are two independent two-parameter Lindley random variables is considered in this paper. The maximum likelihood estimator (MLE) and Bayes estimator of R are obtained. Also, different confidence intervals of R are obtained. Simulation study is performed to compare the different proposed estimation methods. Example in real data is used as practical application of the proposed procedure.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.4
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• pp.256-262
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• 2016

The Weibull is widely used in reliability analysis, and several studies have attempted to improve estimation of the distribution's parameters. least squares estimation (LSE) or Maximum likelihood estimation (MLE) are often used to estimate distribution parameters. However, it has been proven that Bayesian methods are more suitable for small sample sizes than LSE and MLE. In this work, the Weibull parameter estimation accuracy of LSE, MLE, and Bayesian method are compared for sample sets with 3 to 30 data points. The Bayesian method was most accurate for sample sizes under 25, and the accuracy of the Bayesian method was similar to LSE and MLE as the sample size increased.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.1
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• pp.42-51
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• 2011

Poisson model and Gamma-Poisson model are popularly used to analyze statistical behavior from defective data. The methods are based on binary criteria, that is, good or failure. However, manufacturing industries prefer polytomous criteria for classifying manufactured products due to flexibility of marketing. In this paper, I introduce two multivariate Gamma-Poisson(MGP) models and estimation methods of the parameters in the models, which are able to handle polytomous data. The models and estimators are verified on defective pixels of LCD manufacturing. Experimental results show that both the independent MGP model and the multinomial MGP model have excellent performance in terms of mean absolute deviation and the choice of method depends on the purpose of use.

• Journal of the Korean Statistical Society
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• v.27 no.2
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• pp.165-187
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• 1998

Shin and Sarkar (1993, 1994) studied the problem of testing for a unit root in an AR(p) signal observed with MA(q) noise when the MA parameters are known. In this paper we consider the case when the MA parameters are unknown and to be estimated. Test statistics are defined using unit root parameter estimates based on three different estimation methods of Hannan and Rissanen (1982), Kohn (1979) and Shin and Sarkar (1995). An AR(p) process contaminated by MA(q) noise is a .estricted ARMA model, for which Shin and Sarkar (1995) derived an easy-to-compute Newton- Raphson estimator The two-stage estimation p.ocedu.e of Hannan and Rissanen (1982) is used to compute initial parameter estimates in implementing the iterative estimation methods of both Shin and Sarkar (1995) and Kohn (1979). In a simulation study we compare the relative performance of these unit root tests with respect to both size and power for p=q=1.

• Journal of Korea Technology Innovation Society
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• v.13 no.3
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• pp.513-537
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• 2010

According to the "FDI-as-market-discipline" hypothesis, inward FDI acts as a mechanism of change in market structure affecting innovative activities of domestic firms. We used panel KIS data for testing this hypothesis. Binary probit estimation shows that, in contrast to the German case of Bertschek (1995), FDI is insignificant in Korean case for explaining product innovation. 1his result maybe comes from the fact that the industries in Korea are more monopolistic or oligopolistic than those of Germany. Using panel data, we tried random parameter estimation using matrix weighted average of GLS and OLS. The result shows different estimates from cross-section outcome and panel estimation with parameter homogeneity, so we can infer large parameter heterogeneity across firms. But, interpretation for FDI variable is similar across panel and cross-section estimation.