• Journal of the Korean Data and Information Science Society
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• 제8권1호
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• pp.71-77
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• 1997

S independent sample 0,1,2, $\cdots$, s-1 (or stages 0,1,2, $\cdots$, s-1) are available from the Raleigh population. Procedure for predicting any order statistic in the $(s+1)^{th}$ sample is developed by obtaining the predictive distribution at stage s. Bounds for the sample size at stage S, in order to have the variance at stage S less than that at stage (s-1), are obtained.

• Journal of the Korean Data and Information Science Society
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• 제18권4호
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• pp.1191-1203
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• 2007

In this paper, we consider the hypothesis testing for the homogeneity of the shape parameters in the gamma distributions. The noninformative priors such as Jeffreys# prior or reference prior are usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. So we propose the objective Bayesian testing procedure for the homogeneity of the shape parameters based on the fractional Bayes factor and the intrinsic Bayes factor under the reference prior. Simulation study and a real data example are provided.

• 천문학논총
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• 제20권1호
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• pp.109-116
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• 2005

When we measure a source signal in the presence of a background rate that has been independently measured, the usual approach is to obtain an estimate of the background rate by observing an empty part of the sky, and an estimate of the source signal plus background rate by observing the region where a source signal is expected. The source signal rate is then estimated by subtracting the background rate from the source signal plus background rate. However, when the rates or their observation times are small, this procedure can lead to negative estimates of the source signal rate, even when it should produce a positive value. By applying the Bayesian approach, we solve the problem and prove that the most probable value of source signal rate is zero when the observed total count is smaller than the expected background counts. It is also shown that the results from the conventional method is consistent with the most probable value obtained from the Bayesian approach when the source signal is large or the observation time is long enough.

• Journal of information and communication convergence engineering
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• 제7권3호
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• pp.383-391
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• 2009

In this paper, blind equalization using a modified Fuzzy C-Means algorithm with Gaussian Weights (MFCM_GW) is attempted to the heavy noise-corrupted channels. The proposed algorithm can deal with both of linear and nonlinear channels, because it searches for the optimal channel output states of a channel instead of estimating the channel parameters in a direct manner. In contrast to the common Euclidean distance in Fuzzy C-Means (FCM), the use of the Bayesian likelihood fitness function and the Gaussian weighted partition matrix is exploited in its search procedure. The selected channel states by MFCM_GW are always close to the optimal set of a channel even the additive white Gaussian noise (AWGN) is heavily corrupted in it. Simulation studies demonstrate that the performance of the proposed method is relatively superior to existing genetic algorithm (GA) and conventional FCM based methods in terms of accuracy and speed.

• 한국조사연구학회지:조사연구
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• 제9권1호
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• pp.87-100
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• 2008

200여개의 지역구 선거가 동시에 치러지는 국회의원 선거에서 주요정당의 의석 수를 예상해야 할 필요가 있는데, 이제까지는 정당별로 당선확실 선거구 수에 경합 선거구 수를 적당히 더하는 상식적 수준의 셈에 의존하여 왔다. 그러나 선거 예측 조사 자료를 베이즈 추론의 틀에 넣어 활용함으로써 정당 의석 수에 대한 합리적 점 예측과 구간 예측이 가능하다. 2004년의 제 17대 국회의원 선거에 적용하여 이 방법의 실용성을 살펴보았다.

• Journal of the Korean Statistical Society
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• 제30권4호
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• pp.613-635
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• 2001

This paper proposes a skewed multivariate probit model for analyzing a correlated binary response data with covariates. The proposed model is formulated by introducing an asymmetric link based upon a skewed multivariate normal distribution. The model connected to the asymmetric multivariate link, allows for flexible modeling of the correlation structure among binary responses and straightforward interpretation of the parameters. However, complex likelihood function of the model prevents us from fitting and analyzing the model analytically. Simulation-based Bayesian inference methodologies are provided to overcome the problem. We examine the suggested methods through two data sets in order to demonstrate their performances.

• 한국경영과학회지
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• 제31권2호
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• pp.157-167
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• 2006

Estimating the effects of price increase on a company's sales is important task faced by managers. If consumer has prior information on price increase or expects it, there would be stockpiling and subsequent drops in sales. In addition, consumer can suppress demand in the short run. These factors make the sales dynamic and unstable. In this paper we develop a time series model to evaluate the sales patterns with stockpiling and short-term suppression of demand and also propose a forecasting procedure. For estimation, we use panel data and extend the model to Bayesian hierarchical structure. By borrowing strength across cross-sectional units, this estimation scheme gives more robust and reasonable result than one from the individual estimation. Furthermore, the proposed scheme yields improved predictive power in the forecasting of hold-out sample periods.

• Journal of information and communication convergence engineering
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• 제5권1호
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• pp.35-41
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• 2007

In this paper, a modified Fuzzy C-Means (MFCM) algorithm is presented for nonlinear blind channel equalization. The proposed MFCM searches the optimal channel output states of a nonlinear channel, based on the Bayesian likelihood fitness function instead of a conventional Euclidean distance measure. In its searching procedure, all of the possible desired channel states are constructed with the elements of estimated channel output states. The desired state with the maximum Bayesian fitness is selected and placed at the center of a Radial Basis Function (RBF) equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with that of a hybrid genetic algorithm (GA merged with simulated annealing (SA): GASA), and the relatively high accuracy and fast searching speed are achieved.

• Journal of the Korean Statistical Society
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• 제32권3호
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• pp.271-288
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• 2003

In this paper, when the variance of the normal distribution is related to the mean, we develop noninformative priors such as matching priors and reference priors. We prove that the second order matching prior matches alternative coverage probabilities up to the same order and also it is a HPD matching prior. It turns out that one-at-a-time reference prior satisfies a second order matching criterion. Then using these noninformative priors, we develop a Bayesian test procedure for the equality of the means and variances of two independent normal distributions using fractional Bayes factor. Some simulation study is performed, and a real data example is also provided.

• Communications for Statistical Applications and Methods
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• 제29권3호
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• pp.373-391
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• 2022

The distribution of observations in most econometric studies with spatial heterogeneity is skewed. Usually, a single transformation of the data is used to approximate normality and to model the transformed data with a normal assumption. This assumption is however not always appropriate due to the fact that panel data often exhibit non-normal characteristics. In this work, the normality assumption is relaxed in spatial mixed models, allowing for spatial heterogeneity. An inference procedure based on Bayesian mixed modeling is carried out with a multivariate skew-elliptical distribution, which includes the skew-t, skew-normal, student-t, and normal distributions as special cases. The methodology is illustrated through a simulation study and according to the empirical literature, we fit our models to non-life insurance consumption observed between 1998 and 2002 across a spatial panel of 103 Italian provinces in order to determine its determinants. Analyzing the posterior distribution of some parameters and comparing various model comparison criteria indicate the proposed model to be superior to conventional ones.