• Communications for Statistical Applications and Methods
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• v.11 no.2
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• pp.381-397
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• 2004

The marginal likelihood has become an important tool for model selection in Bayesian analysis because it can be used to rank the models. We discuss the marginal likelihood for Poisson regression models that are potentially useful in small area estimation. Computation in these models is intensive and it requires an implementation of Markov chain Monte Carlo (MCMC) methods. Using importance sampling and multivariate density estimation, we demonstrate a computation of the marginal likelihood through an output analysis from an MCMC sampler.

• Journal of the Korean Statistical Society
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• v.26 no.4
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• pp.493-505
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• 1997

The analysis of binary data appears to many areas such as statistics, biometrics and econometrics. In many cases, data are often collected in which some observations are incomplete. Assume that the missing covariates are missing at random and the responses are completely observed. A method to Bayesian analysis of the binary regression model with incomplete data is presented. In particular, the desired marginal posterior moments of regression parameter are obtained using Meterpolis algorithm (Metropolis et al. 1953) within Gibbs sampler (Gelfand and Smith, 1990). Also, we compare logit model with probit model using Bayes factor which is approximated by importance sampling method. One example is presented.

• The Journal of the Korea Contents Association
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• v.13 no.4
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• pp.53-63
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• 2013

This paper presents an importance sampling(IS) embedded experimental frame(EF) design for efficient Monte Carlo (MC) simulation. To achieve IS principles, the proposed EF contains two embedded sub-models, which are classified into Importance Sampler(IS) and Bias Compensator(BC) models. The IS and BC models stand between the existing system model and EF, which leads to enhancement of model reusability. Furthermore, the proposed EF enables to achieve fast stochastic simulation as compared with the crude MC technique. From the abstract two case studies with the utilization of the proposed EF, we can gain interesting experimental results regarding remarkable enhancement of simulation performance. Finally, we expect that this work will serve various content areas for enhancing simulation performance, and besides, it will be utilized as a tool to understand and analyze social phenomena.

• Communications for Statistical Applications and Methods
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• v.29 no.1
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• pp.65-83
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• 2022

Although various statistical methods have been developed to map time-dependent genetic factors, most identified genetic variants can explain only a small portion of the estimated genetic variation in longitudinal traits. Gene-gene and gene-time/environment interactions are known to be important putative sources of the missing heritability. However, mapping epistatic gene-gene interactions is extremely difficult due to the very large parameter spaces for models containing such interactions. In this paper, we develop a Gaussian process (GP) based nonparametric Bayesian variable selection method for longitudinal data. It maps multiple genetic markers without restricting to pairwise interactions. Rather than modeling each main and interaction term explicitly, the GP model measures the importance of each marker, regardless of whether it is mostly due to a main effect or some interaction effect(s), via an unspecified function. To improve the flexibility of the GP model, we propose a novel grid-based method for the within-subject dependence structure. The proposed method can accurately approximate complex covariance structures. The dimension of the covariance matrix depends only on the number of fixed grid points although each subject may have different numbers of measurements at different time points. The deviance information criterion (DIC) and the Bayesian predictive information criterion (BPIC) are proposed for selecting an optimal number of grid points. To efficiently draw posterior samples, we combine a hybrid Monte Carlo method with a partially collapsed Gibbs (PCG) sampler. We apply the proposed GP model to a mouse dataset on age-related body weight.

• Journal of the Korean Data and Information Science Society
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• v.15 no.1
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• pp.227-237
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• 2004

In this paper we presented a Bayesian inference approach for estimating the location and scale parameters of the lognormal distribution using iterative Gibbs sampling algorithm. We also presented estimation of location parameter by two non iterative methods, importance sampling and weighted bootstrap assuming scale parameter as known. The estimates by non iterative techniques do not depend on the specification of hyper parameters which is optimal from the Bayesian point of view. The estimates obtained by more sophisticated Gibbs sampler vary slightly with the choices of hyper parameters. The objective of this paper is to illustrate these tools in a simpler setup which may be essential in more complicated situations.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.34 no.2
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• pp.115-124
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• 2024

Objectives: The aim of this study is to assess indoor air quality within and around buildings and evaluate the health risks associated with exposure to indoor air pollution. The study compares IAQ standards established by the World Health Organization with those set by South Korea's Ministry of Environment and Ministry of Education. Methods: The study utilized an Anderson Sampler and DustTrak^TM II to collect samples of total airborne bacteria and PM in indoor and outdoor environments. Collected samples were analyzed using biological and biochemical methods. Statistical analysis was conducted using SPSS to examine the correlation between airborne bacteria and PM. Results: The study revealed that the concentration of total airborne bacteria in indoor air generally remained below the Ministry of Environment's standard of 800 CFU/m³, although it surpassed this threshold in certain instances. PM concentrations did not exceed the standards. Indoor fine dust concentration was higher when there were people (P<0.05). There was no difference in total floating bacterial concentrations between indoor and outdoor environments (P=0.184). Finally, there was a correlation between fine dust and airborne bacteria concentrations. Conclusion: The study evaluated the concentrations of total airborne bacteria and PM in indoor air, emphasizing the importance of managing IAQ. Further research in various environments is essential to ensure a healthy indoor environment. The findings underscore the need for ongoing research and management to enhance IAQ and create safer and healthier living environments.

• Journal of the Korean Statistical Society
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• v.31 no.2
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• pp.177-198
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• 2002

The estimation of variance components or variance ratios in linear model is an important issue in plant or animal breeding fields, and various estimation methods have been devised to estimate variance components or variance ratios. However, many traits of economic importance in those fields are observed as dichotomous or polychotomous outcomes. The usual estimation methods might not be appropriate for these cases. Recently threshold linear model is considered as an important tool to analyze discrete traits specially in animal breeding field. In this note, we consider a hierarchical Bayesian method for the threshold animal model. Gibbs sampler for making full Bayesian inferences about random effects as well as fixed effects is described to analyze jointly discrete traits and continuous traits. Numerical example of the model with two discrete ordered categorical traits, calving ease of calves from born by heifer and calving ease of calf from born by cow, and one normally distributed trait, birth weight, is provided.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.22 no.4
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• pp.189-195
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• 1989

The ecological studies of the benthic polychaetes were carried out in the follow Sea for the period of August 1982 through February 1986. Special emphasis were placed on quantitative species composition and the importance of polychaetes in the benthic community. Polychaete group ranked numerically high, composing $35.1\~46.4\%$ of the total benthos. In the biomass, echinoderms or mollusks showed as a dominant group, but the range of its seasonal variation was very large. Due to the use of sampling gear, the relative importance of polychaetes was somewhat different. The case of a dredge showed a little lower composition rate of polychaetes than a grab one. This result was caused by high density of benthic animals because the dredge would tow only much more surface sediments than the grab sampler. The present studies included a total of 141 species and the representative polychaetes in this area were Spiophanes bormbyx, Ampharete arctica, Geniada maulata, Nephtys caeca, Nothria iridescens.

• Journal of Korean Society for Atmospheric Environment
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• v.15 no.4
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• pp.485-493
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• 1999

This paper presents the results of the first interlaboratory comparison of ambient particles measurement conducted by 5 laboratories under the framework of Korean Society for Atmospheric Environment(KOSAE) on the May of 1998 in Seoul. Collection of particles less than 10$mu extrm{m}$(PM10) was carried out by two different types of PM10 sampler, and their concentration reported by three laboratories ranged from 36.2~56.05$\mu\textrm{g}$/㎥. Analyses of chemical composition of particles collected by each lab were performed by the destructive and nondestructive instrumental methods. Statistical analysis of the measurement results could not be carried out because a comprehensive QA/QC had not been applied before experiment. The importance of QA/QC as well as the performance of QA/QC for the measurement of PM10 was discussed in detail.

• 대한예방의학회:학술대회논문집
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• 1994.02a
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• pp.585-595
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• 1994

The region of the respiratory tract where inhaled particles deposit can have important implications for the causation of local or systemic toxic effects. For most aerosols of occupational importance, respiratory tract deposition can be predicted from the aerodynamic diameter of the particles. With the advent of cascade impactors, particularly those of personal sampler size, the determination of the aerodynamic diameters of aerosols has become more common. Some limitations of cascade impactor use are well recognized (e.g., particle bounce and substrate overloading) and are generally correctable. However, two important limitations of the instruments may not be receiving adequate attention: relative humidity effects on potentially hygroscopic aerosols and the collection characteristics of fibrous aerosols as compared to their actual deposition site potential. The results of this study, when compared to results of previous controlled laboratory trials, suggest that, while potentially hygroscopic lead aerosols from lead acid battery plant operations do not appear to be affected by changes in plant environmental humidity levels, the potential - exists for significant size changes upon inhalation. Secondly, fibers were detected in aerodynamic size ranges that would be associated with deep lung deposition; however, upon microscopic examination, these same fibers would actually be predicted to deposit in the upper airways. This study suggests that the physicalchemical properties and morphological features of an aerosol should be carefully considered by industrial hygienists before cascade impactors are used in attempts to predict the effects of inhaled aerosols.