• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1309-1317
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• 2013

There are various parameter estimation methods for the generalized exponential distribution under progressive type I interval censoring. Chen and Lio (2010) studied the parameter estimation method by the maximum likelihood estimation method, mid-point approximation method, expectation maximization algorithm and methods of moments. Among those, mid-point approximation method has the smallest mean square error in the generalized exponential distribution under progressive type I interval censoring. However, this method is difficult to derive closed form of solution for the parameter estimation using by maximum likelihood estimation method. In this paper, we propose two type of approximate maximum likelihood estimate to solve that problem. The simulation results show the obtained estimators have good performance in the sense of the mean square error. And proposed method derive closed form of solution for the parameter estimation from the generalized exponential distribution under progressive type I interval censoring.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.1
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• pp.67-75
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• 2011

This paper presents a new test technique for evaluating performance of vehicle detectors with interval estimation, not the conventional point estimation, for presenting statistical confidence interval. The methodology is categorized into three parts; sampling plan, analysis on the characteristic of evaluation indices, and the expression of evaluation results. Even though many statistical sampling plans exist, stratified random sampling is regarded as the most appropriate one, considering the detector performance characteristics that varies with traffic, illumination, and meteorological conditions. No magic bullet exists for evaluation index for detector evaluation, hence the characteristics of evaluation indices were thoroughly analyzed and a reasonable process for choosing the best evaluation index is proposed. Finally, the methodology to express the result of detector evaluation for the entire evaluation period and individual analysis interval is represented, respectively. To overcome the existing drawbacks in point estimation, interval estimation by which statistical confidence interval can be represented is introduced for enhancing statistical reliability of traffic detector evaluation. This research can make vehicle detector scheme improve one step forward.

• International Journal of Contents
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• v.10 no.4
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• pp.69-74
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• 2014

General location aware systems are only applied to indoor and outdoor environments using more than three transmitters to estimate a fixed object location. Those kinds of systems have environmental restrictions that require an already established infrastructure. To solve this problem, an Object Location Estimation (OLE) algorithm based on PTP (Point To Point) communication has been proposed. However, the problem with this method is that deduction of performance parameters is not enough and location estimation is very difficult because of unknown restriction conditions. From experimental tests in this research, we determined that the performance parameters for restriction conditions are a maximum transmission distance of CSS communication and an optimum moving distance interval between personal locations. In this paper, a system applied OLE algorithm based on PTP communication is implemented using a CSS (Chirp Spread Spectrum) communication module. A maximum transmission distance for CSS communication and an optimum moving distance interval between personal locations are then deducted and studied to estimate a fixed object location for generalization.

• Journal of Korean Society of Transportation
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• v.23 no.3 s.81
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• pp.109-123
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• 2005

The goals of this paper are two folds: i) to evaluate whether the data collected by a license plate matching AVI equipment being operated on some segment of a national highway are suitable or not for use in travel time estimation of interrupted traffic flows; ii) to study the statistical methodologies to be used for the determination of the optimal aggregation interval for travel time estimation. In this study it was found that the AVI data are not representative because the data are collected on some selected lanes of a roadway where main traffic is thru-traffic and, thus the AVI data are different from those collected from all lanes in traffic characteristics. For the determination of the optimal aggregation interval for travel time estimation. two statistical methods. namely point estimation and interval estimation. were tested. The test shows that the point estimation method is more sensitive and gives more desirable results in determing the optimal aggregation interval than the interval estimation method. And it turned out that the optimal aggregation interval on interrupted traffic flows has been calculated as 5 minute and thus the existing aggregation interval. 5 minute is proper.

• Journal of Applied Reliability
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• v.16 no.1
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• pp.32-40
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• 2016

Purpose: The purpose of this study is to analyze the effect of sampling points on accuracy of storage reliability estimation for one-shot systems by assuming a weibull distribution as a storage reliability distribution. Also propose method for determining of sampling points for increase the accuracy of reliability estimation. Methods: Weibull distribution was divided into three sections for confirming the possible to estimate the parameters of the weibull distribution only some section's sample. Generate quantal response data for failure data. And performed parameter estimation with quantal response data. Results: If reduce sample point interval of 1 section, increase the accuracy of reliability estimation although sampling only section 1. Even reduce total number of sampling point, reducing sampling time interval of the 1 zone improve the accuracy of reliability estimation. Conclusion: Method to increase the accuracy of reliability estimation is increasing number of sampling and the sampling points. But apply this method to One-shot system is difficult because test cost of one-shot system is expensive. So propose method of accuracy of storage reliability estimation of one-shot system by adjustment of the sampling point. And by dividing the section it could reduce the total sampling point.

• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.1069-1086
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• 2003

This article presents the asymptotic theory of triple sampling procedure as pertain to estimating the shape parameter of Pareto distribution. Both point and confidence interval estimation are considered within the same inference unified framework. We show that this group sampling technique possesses the efficiency of Anscome (1953), Chow and Robbins (1965) purely sequential procedure as well as reduce the number of sampling operations by utilizing Stein (1945) two stages procedure. The analysis reveals that the technique performs excellent as far as the accuracy is concerned. The present problem differs from those considered by many authors, in multistage sampling, in that the final stage sample size and the parameter's estimate become highly correlated and therefore we adopted different approach.

• Journal of the Korean Statistical Society
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• v.31 no.4
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• pp.415-431
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• 2002

A unified framework for statistical inference for the mean of the normal distribution to derive point estimates, confidence intervals and statistical tests is proposed. This optimal design is justified after investigating the basic information and requirements that are possible and impossible to control when specifying practical and statistical requirements. Point estimation is only credible when viewed in the larger context of interval estimation, since the information required for optimal point estimation is unspecifiable. Triple sampling is proposed and justified as a reasonable sampling vehicle to achieve the specifiable requirements within the unified framework.

• Journal of the Korean Data and Information Science Society
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• v.25 no.3
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• pp.643-653
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• 2014

In this paper, we propose some estimators for the extreme value distribution based on the interval method and mid-point approximation method from the progressive Type-I interval censored sample. Because log-likelihood function is a non-linear function, we use a Taylor series expansion to derive approximate likelihood equations. We compare the proposed estimators in terms of the mean squared error by using the Monte Carlo simulation.

• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.989-995
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• 2003

Inference for probability P(Y

• Communications for Statistical Applications and Methods
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• v.26 no.4
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• pp.385-410
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• 2019

This paper proposes a new class of distribution using the concept of exponentiated of distribution function that provides a more flexible model to the baseline model. It also proposes a new lifetime distribution with different types of hazard rates such as decreasing, increasing and bathtub. After studying some basic statistical properties and parameter estimation procedure in case of complete sample observation, we have studied point and interval estimation procedures in presence of type-II censored samples under a classical as well as Bayesian paradigm. In the Bayesian paradigm, we considered a Gibbs sampler under Metropolis-Hasting for estimation under two different loss functions. After simulation studies, three different real datasets having various nature are considered for showing the suitability of the proposed model.