• The Korean Journal of Applied Statistics
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• v.24 no.4
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• pp.677-693
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• 2011

In this paper, we consider Bayesian approaches to zero inflated Poisson model, one of the popular models to analyze zero inflated count data. To generate posterior samples, we deal with a Markov Chain Monte Carlo method using a Gibbs sampler and an exact sampling method using an Inverse Bayes Formula(IBF). Posterior sampling algorithms using two methods are compared, and a convergence checking for a Gibbs sampler is discussed, in particular using posterior samples from IBF sampling. Based on these sampling methods, a real data analysis is performed for Trajan data (Marin et al., 1993) and our results are compared with existing Trajan data analysis. We also discuss model selection issues for Trajan data between the Poisson model and zero inflated Poisson model using various criteria. In addition, we complement the previous work by Rodrigues (2003) via further data analysis using a hierarchical Bayesian model.

• The Korean Journal of Applied Statistics
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• v.21 no.4
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• pp.665-674
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• 2008

Most of existing studies about the small area estimation deal with the estimation of parameters based on cross-sectional data. However, since many official statistics are repeatedly collected at a regular interval of time, for instance, monthly, quarterly, or yearly, we need an alternative model which can handle characteristics of these kinds of data. In this paper, we investigate the generalized estimating equation which can model time-dependency among response variables and is useful to analyze repeated measurement or longitudinal data. We compare with the generalized linear model and the generalized estimating equation through the estimation of unemployment rates of 25 areas in Gyeongsangnam-do and Ulsan. The data consist of the status of employment and some covariates from January to December 2005.

• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.991-1002
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• 2014

Both Bayesian and maximum likelihood methods are efficient for the estimation of regression coefficients of various Tobit regression models (see. e.g. Chib, 1992; Greene, 1990; Lee and Choi, 2013); however, some researchers recognized that the maximum likelihood method tends to underestimate the disturbance variance, which has implications for the estimation of marginal effects and the asymptotic standard error of estimates. The underestimation of the maximum likelihood estimate in a seemingly unrelated Tobit regression model is examined. A Bayesian method based on an objective noninformative prior is shown to provide proper estimates of the disturbance variance as well as other regression parameters

• The Korean Journal of Applied Statistics
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• v.23 no.5
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• pp.823-834
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• 2010

Stock markets perpetually accumulate information. During trading hours the price instantaneously reacts to new information, but accumulated overnight information reacts simultaneously on the opening price. This can create opening price uctuations. This study explores the overnight information e ects on intra-da stock market volatility. GARCH models and the VKOSPI model are provided. Empirical data includes daily opening and closing prices of the KOSPI 200 index and the VKOSPI from March $3^{rd}$ 2008 to June $22^{th}$ 2010. Empirical results show that the VKOSPI signi cantly decrease during trading time when positiv overnight information moves the Korean stock upward. This study provides useful information to investors since the Korea Exchange plans to introduce a futures market for the VKOSPI soon.

• The Korean Journal of Applied Statistics
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• v.23 no.2
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• pp.335-344
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• 2010

Reliability of the estimation is usually damaged in the situation where a linear regression model without spatial dependencies is employed to the spatial data analysis. In this study, we considered the conditional autoregressive model in order to construct spatial association structures and estimate the parameters via the Bayesian approaches. Finally, we compared the performances of the models with spatial effects and the ones without spatial effects. We analyzed the yearly total crime count data measured from each of 25 districts in Seoul, South Korea in 2007.

• The Korean Journal of Applied Statistics
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• v.32 no.5
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• pp.763-782
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• 2019

This paper proposes a probabilistic document ranking model incorporating term dependencies. Document ranking is a fundamental information retrieval task. The task is to sort documents in a collection according to the relevance to the user query (Qin et al., Information Retrieval Journal, 13, 346-374, 2010). A probabilistic model is a model for computing the conditional probability of the relevance of each document given query. Most of the widely used models assume the term independence because it is challenging to compute the joint probabilities of multiple terms. Words in natural language texts are obviously highly correlated. In this paper, we assume a multinomial distribution model to calculate the relevance probability of a document by considering the dependency structure of words, and propose an information retrieval model to rank a document by estimating the probability with the maximum entropy method. The results of the ranking simulation experiment in various multinomial situations show better retrieval results than a model that assumes the independence of words. The results of document ranking experiments using real-world datasets LETOR OHSUMED also show better retrieval results.

• Journal of Korean Biological Nursing Science
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• v.10 no.2
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• pp.176-183
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• 2008

Purpose: The purpose of this study was to identify the effect of Environmental Enrichment (EE) on improvement of motor function in animal models of Parkinson's Disease. Methods: Male C57BL6 mice weighing 25-30 g, at the age of 12 wks were used in this study. The animals were injected MPTP (1-methyl-4-phenyl-1,2,3,6-tetrahydropyridin, 20 mg/kg in saline, i.p.) 4 times a day at every 2 hr, and raised in EE cage for 14 days. On day 14, after behavior test, all mice were sacrificed for immunohistochemistry. All values were expressed as means$\pm$S.E.M. Statistical significance was evaluated using a one way ANOVA followed by Sheffe test. Results: There was a significant difference between the experimental group and the control group in the behavior test. Also EE significantly reduced of TH positive cell loss in Substantia nigra pars compacta as compared to the result of MPTP treatment. Conclusion: Based on these findings, it is reasonable to assume that the environmental enrichment prevents dopaminergic neuronal loss and improves disarrangement of motor function and behavioral disability induced by MPTP.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.3
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• pp.92-101
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• 2012

Trip demands and patterns on weekends have been changed significantly over the past decade due to the income growth and the spread of the 5-day workweek in Korea. The increased weekend trips for shopping, leisure activities, entertainment and friendship have exacerbated traffic congestion in major highways or principal arterial roads from Friday afternoon through Sunday. Therefore, it is necessary to focus on travel demand forecasts and transport policies for weekend trips by investigating specific characteristics of the trips. Previous research efforts focus on simple analysis of characteristics of weekend trips and comparison of travel characteristics between weekdays and weekends. The paper analyzes the differences between weekday and weekend trips via statistical analyses to derive multiple types of characteristics of weekend trips, and develops Tobit models to identify key factors that may affect the number of trips, using Seoul city's weekend trip survey data in 2006. The model results show that weekend trips appear differently from weekdays by household or individual characteristics. Age, residence area and type of residence affected the number of trips, regardless of the type of the day, whereas gender, occupation, income, presence of household vehicle showed different impacts on trips between weekdays and weekends.

• Journal of Technologic Dentistry
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• v.37 no.1
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• pp.9-15
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• 2015

Purpose: The purpose of this study was to compare the accuracy of the maxillary three-unit fixed dental prosthesis (FDPs) made using two CAD/CAM milling machines : DCM Group(Dentaim CAD/CAM milling machine), WCM Group(Wieland CAD/CAM milling machine). Methods: Each of 10 duplicate models was scanned by blue light scanner(Identica, Medit, Korea), and the three-unit FDPs (STL file) was designed using DelcamCAD. A total of 20 three-unit FDPs was fabricated, comprising 2 groups of 10 specimens each (shrinkage ratio is 1:1). The first three-unit FDPs STL file was used as a CAD reference model (CRM). Obtained STL files by scanning the inner surface of three-unit FDPs were convened into the point clouds-ASC II files. Discrepancies between the point clouds and CRM were measured by superimposition software. Statistical methods to analyze the data were used non-parametric method. The mean (SD) values were compared by a Mann-Whitney U-test. Type one error rate was set at 0.05. Results: WCM group had small discrepancies with $2.17{\mu}m$ of mean value compared to $4.44{\mu}m$ in DCM group. The accuracy values between the two groups showed a sratistically significant difference (Table 2, p<.05). Conclusion: The accuracy of the three-unit fixed dental prosthesis(FDPs) made of two CAD/CAM milling machines were statistically different. Accuracy with which the prosthesis made of WCM group was superior.

• Structural Engineering and Mechanics
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• v.26 no.6
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• pp.709-723
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• 2007

Considering the vast usage of time-history dynamic analyses to calculate structural responses and lack of sufficient and suitable earthquake records, generation of artificial accelerograms is very necessary. The main target of this paper is to present a novel method based on nonstationary Kanai-Tajimi model and wavelet transform to generate more artificial earthquake records, which are compatible with target spectrum. In this regard, the generalized nonstationary Kanai-Tajimi model to include the nonstationary evaluation of amplitude and dominant frequency of ground motion and properties of wavelet transform is used to generate ground acceleration time history. Application of the method for El Centro 1940 earthquake and two Iranian earthquakes (Tabas 1978 and Manjil 1990) is presented. It is shown that the model and identification algorithms are able to accurately capture the nonstationary features of these earthquake accelerograms. The statistical characteristics of the spectral response of the generated accelerograms are compared with those for the actual records to demonstrate the effectiveness of the method. Also, for comparison of the presented method with other methods, the response spectra of the synthetic accelerograms compared with the models of Fan and Ahmadi (1990) and Rofooei et al. (2001) and it is shown that the response spectra of the synthetic accelerograms with the method of this paper are close to those of actual earthquakes.