• Journal of the Korean Data and Information Science Society
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• v.10 no.1
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• pp.119-133
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• 1999

A Markov Chain Monte Carlo method is developed to compute the software reliability model. We consider computation problem for determining of posterior distibution in Bayseian inference. Metropolis algorithms along with Gibbs sampling are proposed to preform the Bayesian inference of the Mixed model with record value statistics. For model determiniation, we explored the prequential conditional predictive ordinate criterion that selects the best model with the largest posterior likelihood among models using all possible subsets of the component intensity functions. To relax the monotonic intensity function assumptions. A numerical example with simulated data set is given.

• Journal of Korea Water Resources Association
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• v.44 no.2
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• pp.125-134
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• 2011

The paper is to estimate willingness-to-pay (WTP) for residential water quality improvement in Busan, using non-parametric approach. There are several significant advantages of non-parametric approach, compared to parametric methods. That is, no probability distribution assumption is necessary so that there are no needs to assume or test goodness of fit, model specification and heteroscedasticity statistically. For the reliability and the validity of contingent valuation method a survey was conducted for 665 respondents, who were sampled by stratified random sampling method, by personal interview method. The result of mean WTP for residential water quality improvement in Busan was estimated to be 3,190 won to 3,331 won per month per household, while median WTP being 1,750 won. Provided that our sample is broadly representative of the Busan's population, an estimate of the annual aggregated benefit of residential water improvement for all Busan households is approximately 50.2 billion won in case of mean WTP or 27.5 billion won in case of median WTP.

• Journal of the Korean earth science society
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• v.40 no.3
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• pp.259-271
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• 2019

A statistical downscaling method was adopted in order to establish the high-resolution wave prediction system in the East Sea coastal area. This system used forecast data from the Global Wave Watch (GWW) model, and the East Sea and Busan Coastal Wave Watch (CWW) model operated by the Korea Meteorological Administration (KMA). We used the CWW forecast data until three days and the GWW forecast data from three to seven days to implement the statistical downscaling method (inverse distance weight interpolation and conditional merge). The two-dimensional and station wave heights as well as sea surface wind speed from the high-resolution coastal prediction system were verified with statistical analysis, using an initial analysis field and oceanic observation with buoys carried out by the KMA and the Korea Hydrographic and Oceanographic Agency (KHOA). Similar to the predictive performance of the GWW and the CWW data, the system has a high predictive performance at the initial stages that decreased gradually with forecast time. As a result, during the entire prediction period, the correlation coefficient and root mean square error of the predicted wave heights improved from 0.46 and 0.34 m to 0.6 and 0.28 m before and after applying the statistical downscaling method.

• Tunnel and Underground Space
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• v.15 no.4 s.57
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• pp.264-274
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• 2005

The optimum blasting pattern to excavate a quarry efficiently and economically can be determined based on the minimum production cost which is generally estimated according to rock fragmentation. Therefore it is a critical problem to predict fragment size distribution of blasted rocks over an entire quarry. By comparing various prediction models, it can be ascertained that the result obtained from Kuz-Ram model relatively coincides with that of field measurements. Kuz-Ram model uses the concept of rock factor to signify conditions of rock mass such as block size, rock jointing, strength and others. For the evaluation of total production cost, it is imperative to estimate 3-D spatial distribution of rock factor for the entire quarry. In this study, a sequential indicator simulation technique is adopted for estimation of spatial distribution of rock factor due to its higher reproducibility of spatial variability and distribution models than Kriging methods. Further, this can reduce the uncertainty of predictor using distribution information of sample data The entire quarry is classified into three types of rock mass and optimum blasting pattern is proposed for each type based on 3-D spatial distribution of rock factor. In addition, plane maps of rock factor distribution for each ground levels is provided to estimate production costs for each process and to make a plan for an optimum blasting pattern.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1201-1212
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• 2016

Value at Risk (VaR) for market risk management is a favorite method used by financial companies; however, there are some problems that cannot be explained for the amount of loss when a specific investment fails. Conditional Tail Expectation (CTE) is an alternative risk measure defined as the conditional expectation exceeded VaR. Multivariate loss rates are transformed into a univariate distribution in real financial markets in order to obtain CTE for some portfolio as well as to estimate CTE. We propose multivariate CTEs using multivariate quantile vectors. A relationship among multivariate CTEs is also derived by extending univariate CTEs. Multivariate CTEs are obtained from bivariate and trivariate normal distributions; in addition, relationships among multivariate CTEs are also explored. We then discuss the extensibility to high dimension as well as illustrate some examples. Multivariate CTEs (using variance-covariance matrix and multivariate quantile vector) are found to have smaller values than CTEs transformed to univariate. Therefore, it can be concluded that the proposed multivariate CTEs provides smaller estimates that represent less risk than others and that a drastic investment using this CTE is also possible when a diversified investment strategy includes many companies in a portfolio.

• Environmental and Resource Economics Review
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• v.22 no.1
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• pp.147-177
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• 2013

Annual total values and thereby assets values of natural resources are determined by sample household WTP estimates and the extent of market. In the current domestic practice of CVM, total numbers of national households were used as the target population to measure total economic values including non-use values. This study proposed an alternative method of calculating potential user groups based on distributions of residential area of visitors in the sample using 4 provincial parks in the Chon Buk area as cases. The sample mean of WTP of Moak Mt. visitors, who are mostly from the nearby Chon Buk provincial area, was estimated to be about 8,215 won. On the other hand, the mean of WTP of Sun Woon Mt., whose visitors are evenly distributed from all over the country, was about 4,693 won. When applied national households as the target population, annual total benefits and thereby asset values of Moak Mt. was high enough to be 86 billion and 1.6 trillion won respectively. However, those of Sun Woon Mt. was low to be 52 billion and 1 trillion. On the contrary, when applied potential user groups of each park as the extent of market, annual total benefits and asset values of Sun Woon Mt. was reversed to be high--23 billion won and 400 billion won respectively. However, those of Moak Mt. was lowered to be 10 billion won and 200 billion won. Furthermore, asset values of the same park were differed by 2 to 8 times according to the way of setting the extent of market.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.17 no.3
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• pp.178-187
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• 2005

A reliability analysis model f3r studying the influence of joint distribution of wave heights and periods on wave un-up is presented in this paper. From the definition of failure mode related to wave run-up, a reliability function may be formulated which can be considered uncertainties of water level. In particular, the reliability analysis model can be directly taken into account statistical properties and distributions of wave periods by considering wave period in the reliability function to be a random variable. Also, variations of wave height distribution conditioned to mean wave periods can be taken into account correctly. By comparison of results of additional reliability analysis using extreme distributions with those resulted from joint distribution of wave height and periods, it is found that probabilities of failure evaluated by the latter is larger than those by the former. Although the freeboard of sloped-breakwater structures can be determined by extreme distribution based on the long-term measurements, it may be necessary to investigate additionally into wave run-up by using the present reliability analysis model formulated to consider joint distribution of a single storm event. In addition, it may be found that the effect of spectral bandwidth parameter on reliability index may be little, but the effect of wave height distribution conditioned to mean wave periods is straightforward. Therefore, it may be confirmed that effects of wave periods on the probability of failure of wave run-up may be taken into account through the conditional distribution of wave heights. Finally, the probabilities of failure with respect to freeboard of sloped-breakwater structures can be estimated by which the rational determination of crest level of sloped-breakwater structures may be possible.

• The Korean Journal of Applied Statistics
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• v.6 no.2
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• pp.341-353
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• 1993

As an estimator of the conditional probability of discovering a new species at the next observation after a sample of certain size is taken, the one proposed by Good(1953) has been most widely used. Recently, Clayton and Frees(1987) showed via simulation that their nonparametric maximum likelihood estimator(NPMLE) has smaller MSE than Good's estimator when the population is relatively nonuniform. Lee(1989) proved that their conjecture is asymptotically true for truncated geometric population distributions. One shortcoming of the NPMLE, however, is that it has a considerable amount of negative bias. In this study we proposed a bias-corrected version of the NPMLE for virtually all realistic population distributions. We also showed that it has a smaller asymptotic MSE than Good's extimator except when the population is very uniform. A Monte Carlo simulation was performed for small sample sizes, and the result supports the asymptotic results.

• The Korean Journal of Applied Statistics
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• v.35 no.2
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• pp.311-325
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• 2022

For count responses, the situation of excess zeros often occurs in various research fields. Zero-inflated model is a common choice for modeling such count data. Bayesian inference for the zero-inflated model has long been recognized as a hard problem because the form of conditional posterior distribution is not in closed form. Recently, however, Pillow and Scott (2012) and Polson et al. (2013) proposed a Pólya-Gamma data-augmentation strategy for logistic and negative binomial models, facilitating Bayesian inference for the zero-inflated model. We apply Bayesian zero-inflated negative binomial regression model to longitudinal pharmaceutical data which have been previously analyzed by Min and Agresti (2005). To facilitate posterior sampling for longitudinal zero-inflated model, we use the Pólya-Gamma data-augmentation strategy.

• The Korean Journal of Financial Management
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• v.20 no.2
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• pp.95-126
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• 2003

This paper introduces multifractal processes and presents the empirical investigation of the multifractal asset pricing. The multifractal stock price process contains long-tails which focus on Levy-Stable distributions. The process also contains long-dependence, which is the characteristic feature of fractional Brownian motion. Multifractality introduces a new source of heterogeneity through time-varying local reqularity in the price path. This paper investigates multifractality in stock prices. After finding evidence of multifractal scaling, the multifractal spectrum is estimated via the Legendre transform. The distinguishing feature of the multifractal process is multiscaling of the return distribution's moments under time-resealing. More intensive study is required of estimation techniques and inference procedures.