• The Korean Journal of Applied Statistics
• /
• v.27 no.6
• /
• pp.1003-1016
• /
• 2014

Proper missing data imputation is an important procedure to obtain superior results for data analysis based on survey data. This paper deals with both a model based imputation method and model estimation method. We utilized a Bayesian method to solve a boundary solution problem in which we applied a maximum likelihood estimation method. We also deal with a missing mechanism model selection problem using forecasting results and a comparison between model accuracies. We utilized MWPE(modified within precinct error) (Bautista et al., 2007) to measure prediction correctness. We applied proposed ML and Bayesian methods to the Korean presidential election exit poll data of 2012. Based on the analysis, the results under the missing at random mechanism showed superior prediction results than under the missing not at random mechanism.

• The Korean Journal of Applied Statistics
• /
• v.22 no.4
• /
• pp.735-744
• /
• 2009

In this paper, we introduce a fast approach for Bayesian detection of change points in long-memory processes. Since a heavy computation is needed to evaluate the likelihood function of long-memory processes, a method for simplifying the computational process is required to efficiently implement a Bayesian inference. Instead of estimating the parameter, we consider selecting a element from the set of possible parameters obtained by categorizing the parameter space. This approach simplifies the detection algorithm and reduces the computational time to detect change points. Since the parameter space is (0, 0.5), there is no big difference between the result of parameter estimation and selection under a proper fractionation of the parameter space. The analysis of Nile river data showed the validation of the proposed method.

• Journal of the Korean Data and Information Science Society
• /
• v.28 no.3
• /
• pp.483-492
• /
• 2017

Precipitation is one of key components in hydrological modeling and water balance studies. A comprehensive, optimized and sustainable water balance monitoring requires the availability of accurate precipitation data. The amount of precipitation measured in a gauge is less than the actual precipitation reaching the ground. The objective of this study is to determine the wind-induced under-catch of solid precipitation and develop a continuous adjustment function for measurements of all types of winter precipitation (from rain to dry snow), which can be used for operational measurements based on data available at standard automatic weather stations. This study provides Bayesian analysis for the systematic structure of catch ratio in precipitation measurement.

• Journal of Korean Society of Transportation
• /
• v.22 no.7 s.78
• /
• pp.71-78
• /
• 2004

This paper presents a game-theoretic model of information transmission for variable message sign(VMS) operations. There are one VMS operator and many drivers as players. Operator wants to minimize the total travel time while the drivers want to minimize their own travel time. The operator who knows the actual traffic situation offers information strategically. The drivers evaluate the information from operator, and then choose the route. We model this situation as a cheap-talk game which is a simplest form of Bayesian game. We show that there is a possibility that the operator can improve the traffic efficiency by manipulating the electric signs at times. Indeed, it is an equilibrium of the game. This suggests that the operator must consider the strategic use of VMS system seriously.

• Journal of the Korean Data and Information Science Society
• /
• v.21 no.6
• /
• pp.1191-1201
• /
• 2010

In this paper, we analyze the impact on quitting one's first job based on "Graduates Occupational Mobility Survey" data given by Korea Employment Information Service. According to the survey, there are a large number of questionnaires on quitting one's first job and so it is not easy to choose among them. We will investigate model selection criteria and apply the procedure proposed by Shtatland et al. (2003) to identify the final model.

• The Korean Journal of Applied Statistics
• /
• v.24 no.6
• /
• pp.1149-1160
• /
• 2011

Model selection and hypothesis testing problems in Bayesian inference are still debated between scholars. Bayesian factors traditionally used as a criterion in Bayesian hypothesis testing and model selection, are easy to understand but sometimes hard to compute. In addition, there are other model selection criterions such as DIC(Deviance Information Criterion) by Spiegelhalter et al. (2002) and Bayesian P-values for testing. In this paper, we briefly introduce the Bayesian hypothesis testing and model selection procedure. In addition we have applied a Bayesian inference to Swiss banknote data by a fitting logistic regression model and computing several test statistics to see if they provide consistent results.

• The Transactions of the Korea Information Processing Society
• /
• v.6 no.8
• /
• pp.2060-2071
• /
• 1999

The complicate software failure system is defined to the superposition of the points of failure from several component point process. Because the likelihood function is difficulty in computing, we consider Gibbs sampler using iteration sampling based method. For each observed failure epoch, we applied to latent variables that indicates with component of the superposition mode. For model selection, we explored the posterior Bayesian criterion and the sum of relative errors for the comparison simple pattern with superposition model. A numerical example with NHPP simulated data set applies the thinning method proposed by Lewis and Shedler[25] is given, we consider Goel-Okumoto model and Weibull model with GOS, inference of parameter is studied. Using the posterior Bayesian criterion and the sum of relative errors, as we would expect, the superposition model is best on model under diffuse priors.

• Journal of Korean Society for Quality Management
• /
• v.27 no.3
• /
• pp.125-141
• /
• 1999

Bayesian inference and model selection method for software reliability growth models are studied. Software reliability growth models are used in testing stages of software development to model the error content and time intervals between software failures. In this paper, we could avoid the multiple integration by the use of Gibbs sampling, which is a kind of Markov Chain Monte Carlo method to compute the posterior distribution. Bayesian inference and model selection method for Jelinski-Moranda and Goel-Okumoto and Schick-Wolverton models in software reliability with Poisson prior information are studied. For model selection, we explored the relative error.

• Environmental and Resource Economics Review
• /
• v.11 no.1
• /
• pp.99-119
• /
• 2002

As an alternative to classical maximum likelihood approach for analyzing dichotomous choice contingent valuation (DCCV) data, this paper develops a Bayesian approach. By using the idea of Gibbs sampling and data augmentation, the approach enables one to perform exact inference for DCCV models. A by-product from the approach is welfare measure, such as the mean willingness to pay, and its confidence interval, which can be used for policy analysis. The efficacy of the approach relative to the classical approach is discussed in the context of empirical DCCV studies. It is concluded that there appears to be considerable scope for the use of the Bayesian analysis in dealing with DCCV data.

• The KIPS Transactions:PartD
• /
• v.11D no.6
• /
• pp.1269-1276
• /
• 2004

The Parameter Estimation for software existing reliability models, Goel-Okumoto, Yamada-Ohba-Osaki model was reviewed and Rayleigh model based on Rayleigh distribution was studied. In this paper, we discusses comparison of parameter estimation using maximum likelihood estimator and Bayesian estimation based on Gibbs sampling to analysis of the estimator' pattern. Model selection based on sum of the squared errors and Braun statistic, for the sake of efficient model, was employed. A numerical example was illustrated using real data. The current areas and models of Superposition, mixture for future development are also employed.