• 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.

• The Korean Journal of Applied Statistics
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• v.20 no.3
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• pp.541-550
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• 2007

One of main aspects of time series analysis is to forecast future values of series based on values up to a given time. The prediction interval for future values is usually obtained under the normality assumption. When the assumption is seriously violated, a transformation of data may permit the valid use of the normal theory. We investigate the prediction problem for future values in the original scale when transformations are applied in ARMA models. In this paper, we introduce the methodology based on Yeo-Johnson transformation to solve the problem of skewed data whose modelling is relatively difficult in the analysis of time series. Simulation studies show that the coverage probabilities of proposed intervals are closer to the nominal level than those of usual intervals.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.11
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• pp.479-485
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• 2017

This study estimated the non-use values of the Gum river estuary which are not related to the direct or indirect use of the Gum river estuary using the contingent valuation method (CVM). The non-use values of the Gum river estuary were explained and asked to be evaluated in the CVM questionnaire and estimates of the WTPs(willingness-to-pay) were elicited using the Turnbull nonparametric estimation methods on the dichotomous choice CV data. Results found the Turnbull lower bounded mean WTP per year for non-use value of the Gum river estuary was estimated at 5,822 won (95% C.I. 5,295 ~ 6,349 won) from single dichotomous CV data, and 6,205 won (95% C.I. 5,701 ~ 6,710 won) from double dichotomous CV data. The mean of two WTP estimates, 6,014 won (95% C.I. 5,498 ~ 6,529 won), was used to calculate the annual total non-use value of the Gum river estuary. Therefore, the non-use value of the Gum river estuary was estimated at 220.3 billion won (95% C.I. 201.4 - 239.2 billion won) annually. This non-use value of the Gum river estuary was composed of the bequest value totaling 68.3 billion won (95% C.I. 62.5 - 74.2 billion won), the existence value of 58.0 billion won (95% C.I. 53.0 - 63.0 billion won), the option value of 57.7 billion won (95% C.I. 52.7 - 62.6 billion won), and the vicarious consumption value totaling 36.3 billion won (95% C.I. 33.1 - 39.4 billion won).

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1109-1115
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• 2010

In this paper, exact confidence interval of hyper-geometric parameter, that is the probability of success p in the population is discussed. Usually, binomial distribution is a well known discrete distribution with abundant usage. Hypergeometric distribution frequently replaces a binomial distribution when it is desirable to make allowance for the finiteness of the population size. For example, an application of the hypergeometric distribution arises in describing a probability model for the number of children attacked by an infectious disease, when a fixed number of them are exposed to it. Exact confidence interval estimation of hypergeometric parameter is reviewed. We consider the performance of exact confidence interval estimates of hypergeometric parameter in terms of actual coverage probability by small sample Monte Carlo simulation.

• The Korean Journal of Applied Statistics
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• v.16 no.2
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• pp.377-393
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• 2003

Several confidence interval estimates for the difference of two binomial proportions were introduced. Bootstrap confidence interval is also suggested. We examined the over estimation property of approximate intervals and under estimation trend of exact intervals for the difference of proportions. We compared these confidence intervals based on the average coverage probability, expected width and skewness measure. Particularly actual coverage probability were calculated by using the prior distribution of parameters. Monte Carlo simulation for small sample size is conducted. Some interesting contour plots of average coverage probability and marginal plots for several interval estimates are presented.

• Journal of Wetlands Research
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• v.10 no.1
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• pp.11-20
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• 2008

In this study the estimation method for stream hydraulic characteristics which is served as the input data set for running QualKo water quality model is investigated. The conventional approach for estimating such hydraulic parameters is to use the data set from the last cross section in each reach. However, it is shown that in order to represent correctly flow velocity profiles or the travel time in streams, hydraulic parameters of QualKo model should be estimated with all cross section data set within the corresponding reach. In addition, the unsuitable estimation of hydraulic parameters at some reaches has influence on the water quality predictions at the corresponding reaches, and the errors of water quality predictions are propagated toward the downstream without any error attenuation.

• Journal of Educational Research in Mathematics
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• v.24 no.3
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• pp.375-385
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• 2014

This study compares the confidence interval estimation of population mean with that of population ratio, and considers whether these two estimations ensures consistency. As a result, this study suggests the following acquisition method of consistency : dealing with population mean and population ratio in the same mode, substituting the observed or experimental value of sample standard deviation for standard deviation in population in setting a confidence interval of both population mean and population ratio, and distinguishing population ratio $\hat{P}$ from its observed vale $\hat{p}$.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.29 no.1
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• pp.62-66
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• 2017

The interest on the potential earthquake magnitude and the request on the earthquake-resistant design examination for coastal structures are emerged because of the recently occurred magnitude 5.8 earthquake in Gyeoung-Ju, Korea. In this study, the magnitude and its confidence intervals with the return periods are estimated using the KMA earthquake magnitude data (over 3.5 and 4.0 in magnitude) by the non-parametric extreme value analysis. In case of using the "over 4.0" data set, the estimated magnitudes on the 50- and 100-years return periods are 5.81 and 5.94, respectively. Their 90% confidence intervals are estimated to be 5.52-6.11, 5.62-6.29, respectively. Even though the estimated magnitudes have limitations not considering the spatial distribution, it can be used to check the stability of the diverse coastal structures in the perspective of the life design because the potential magnitude and its confidence intervals in Korea are estimated based on the available 38-years data by the extreme value analysis.

• 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.

• The Korean Journal of Applied Statistics
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• v.11 no.1
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• pp.151-161
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• 1998

We study the bootstrap interval estimation for survival function in the Koziol-Green model. We construct the approximate bootstrap confidence intervals for survival function and prove the strong consistency for the bootstrap estimator of survival function. Finally we show that the approximate bootstrap confidence intervals are better in terms of coverage probability than confidence intervals based on asymptotic normal distribution and transformations of survival function via Monte Carlo simulation study.