• Journal of the Korean Data and Information Science Society
• /
• 제19권2호
• /
• pp.577-585
• /
• 2008

This paper suggests a marginal probability model for analyzing repeated polytomous response data when some factors are nested in others in treatment structures on a larger experimental unit. As a repeated measures factor, time is considered on a smaller experimental unit. So, two different experiment sizes are considered. Each size of experimental unit has its own design structure and treatment structure, and the marginal probability model can be constructed from the structures for each size of experimental unit. Weighted least squares(WLS) methods are used for estimating fixed effects in the suggested model.

• Journal of the Korean Data and Information Science Society
• /
• 제20권1호
• /
• pp.191-202
• /
• 2009

In this study, we drive the one dimensional marginal transform function, probability density function and probability distribution function for the random variables $T_{{\xi}N}$ (Time taken by the servers during the vacations), ${\xi}_N$(Number of vacations taken by the servers) and ${\eta}_N$(Number of customers or units arrive in the system) by controlling the variability of two random variables simultaneously.

• 응용통계연구
• /
• 제14권1호
• /
• pp.25-37
• /
• 2001

세 처리, 세 기간을 갖는 3$\times$3 교차실험에서 c($\geq$3)개의 범주를 가진 자료의 분석에 사용될 수 있는 주변확률모형을 제안한다. 이 모형은 Kenward and Jones(1991)의 결합확률 모형의 대조물 (counterpart)로 사용될 수 있고 2항 변수를 갖는 3$\times$3 교차실험에서 처리 효과를 분석하기 위한 Balagtas et al(1995)의 일변량주변로지트모형의 일반화이다. 세 종류의 링크변화를 사용하여 주변확률모형방정식의 구성된다. 링크변환행렬과 모형행렬을 구성하는 방법이 주어지고, 모수의 추정이 논의된다. 제안된 모형을 Kenward and Jones 자료의 분석에 응용한다.

• 한국정보전자통신기술학회논문지
• /
• 제13권2호
• /
• pp.95-101
• /
• 2020

In this paper, we consider a group testing (GT) framework which is to find a set of defective samples out of a large number of samples. To handle this framework, we propose a maximum product detection algorithm (MPDA) which is based on maximum a posteriori probability (MAP). The key idea of this algorithm exploits iterative detection to propagate belief to neighbor samples by exchanging marginal probabilities between samples and output results. The belief propagation algorithm as a conventional approach has been used to detect defective samples, but it has computational complexity to obtain the marginal probability in the output nodes which combine other marginal probabilities from the sample nodes. We show that the our proposed MPDA provides a benefit to reduce computational complexity up to 12% in runtime, while its performance is only slightly degraded compared to the belief propagation algorithm. And we verify the simulations to compare the difference of performance.

• Communications for Statistical Applications and Methods
• /
• 제27권6호
• /
• pp.675-688
• /
• 2020

In survival analysis of observational data, the inverse probability weighting method and the Cox proportional hazards model are widely used when estimating the causal effects of multiple-valued treatment. In this paper, the two kinds of weights have been examined in the inverse probability weighting method. We explain the reason why the stabilized weight is more appropriate when an inverse probability weighting method using the generalized propensity score is applied. We also emphasize that a marginal hazard ratio and the conditional hazard ratio should be distinguished when defining the hazard ratio as a treatment effect under the Cox proportional hazards model. A simulation study based on real data is conducted to provide concrete numerical evidence.

• 대한수학회보
• /
• 제44권2호
• /
• pp.265-270
• /
• 2007

The modern approach for wavelets imposes a Bayesian prior model on the wavelet coefficients to capture the sparseness of the wavelet expansion. The idea is to build flexible probability models for the marginal posterior densities of the wavelet coefficients. In this note, we derive exact expressions for a popular model for the marginal posterior density.

• Journal of the Korean Data and Information Science Society
• /
• 제13권2호
• /
• pp.317-328
• /
• 2002

We first derive group ordering reference priors in a two-way mixed-effects analysis of variance (ANOVA) model. We show that posterior distributions are proper and provide marginal posterior distributions under reference priors. We also examine whether the reference priors satisfy the probability matching criterion. Finally, the reference prior satisfying the probability matching criterion is shown to be good in the sense of frequentist coverage probability of the posterior quantile.

• Journal of the Korean Data and Information Science Society
• /
• 제26권2호
• /
• pp.367-376
• /
• 2015

데이터마이닝 기법 중의 하나인 군집분석은 다양한 특성을 지닌 관찰대상에 대해 유사성을 바탕으로 동질적인 군집으로 묶은 후, 동일 군집에 속해 있는 공통된 특성을 조사하는데 이용되는 기법이다. 본 논문에서는 주변 확률을 고려하지 않는 확률적 흥미도 측도 기반 유사성 측도인 Yule I과 II, Michael, Digby, Baulieu, 그리고 Dispersion 측도에 대해 상한 및 하한을 설정함으로써 이들의 대소관계를 규명하였다. 그 결과, 세 가지 유형의 대소 관계가 성립한다는 사실을 수식의 증명뿐만 아니라 실제 데이터 및 모의실험 데이터에 의해서도 확인할 수 있었다. 이들 측도들은 각 경계에 있는 측도와는 더욱 더 유사한 값을 가지므로 각 측도의 상한 및 하한은 여러 가지 측도들을 분류하는 도구가 되며, 실제 값의 관점에서 각 측도들의 관계를 알게 되면 주어진 알고리즘의 안정화에 도움이 될 수 있을 것이다.

• Communications for Statistical Applications and Methods
• /
• 제12권2호
• /
• pp.395-411
• /
• 2005

In this paper, we develop the Jeffreys' prior, reference prior and the the probability matching priors for the difference of intraclass correlation coefficients in familial data. e prove the sufficient condition for propriety of posterior distributions. Using marginal posterior distributions under those noninformative priors, we compare posterior quantiles and frequentist coverage probability.

• 응용통계연구
• /
• 제25권5호
• /
• pp.719-731
• /
• 2012

Agreement analysis is conducted to assess reliability among rating results performed repeatedly on the same subjects by one or more raters. The kappa statistic is commonly used when rating scales are categorical. The simple and weighted kappa statistics are used to measure the degree of agreement between two raters, and the generalized kappa statistics to measure the degree of agreement among more than two raters. In this paper, we compare the performance of four different generalized kappa statistics proposed by Fleiss (1971), Conger (1980), Randolph (2005), and Gwet (2008a). We also examine how sensitive each of four generalized kappa statistics can be to the marginal probability distribution as to whether marginal balancedness and/or homogeneity hold or not. The performance of the four methods is compared in terms of the relative bias and coverage rate through simulation studies in various scenarios with different numbers of raters, subjects, and categories. A real data example is also presented to illustrate the four methods.