• Communications for Statistical Applications and Methods
• /
• 제22권6호
• /
• pp.625-637
• /
• 2015

We develop a Bayesian clustering procedure based on a Dirichlet process prior with cluster specific random effects. Gibbs sampling of a normal mixture of linear mixed regressions with a Dirichlet process was implemented to calculate posterior probabilities when the number of clusters was unknown. Our approach (unlike its counterparts) provides simultaneous partitioning and parameter estimation with the computation of the classification probabilities. A Monte Carlo study of curve estimation results showed that the model was useful for function estimation. We find that the proposed Dirichlet process mixture model with cluster specific random effects detects clusters sensitively by combining vague edges into different clusters. Examples are given to show how these models perform on real data.

• 응용통계연구
• /
• 제30권1호
• /
• pp.57-68
• /
• 2017

대량의 데이터에 있어 전반적인 특성 및 구조를 파악하는데 유용하기 때문에 다양한 분야에서 군집분석을 사용하고 있다. Dempster 등 (1977)에서 정의된 expectation-maximization(EM) 알고리즘은 가장 보편적으로 사용되는 군집분석 방법이다. 선형모형의 유한혼합물(finite mixture of linear model) 기법 또한 군집분석 방법 중 많이 사용되는 방법이며 베이지안 군집방법은 Bernardo와 Giron (1988)이 군집에 대한 가중치 확률만 모를 경우 처음 적용하였다. 우리는 이 연구에서 일반적인 선형모형의 유한혼합물이 아닌 군집특정(cluster-specific) 변량효과를 모형에 포함하여 베이지안 분석방법인 깁스표집법(Gibbs sampling)을 사용한다. 제안한 모형의 특성 및 표집법에 대하여 설명하였고 모의실험 및 실제 데이터 분석을 통하여 모형의 유용성을 파악하였다. Hurn 등 (2003)의 CO2 데이터에 모형을 적용하여 변량효과가 없는 모형, 개체특정(subject-specific) 변량효과 모형과 비교하였다.

• The Journal of Asian Finance, Economics and Business
• /
• 제8권1호
• /
• pp.841-850
• /
• 2021

This study aims to evaluate the relationship between bank capital, efficiency, and risk in Islamic banks. We use data from 129 Islamic banks in the world, retrieved from various data sources. We retrieved specific banking data from Moody's Analytics BankFocus and Thomson Reuters Eikon, while data at the country level was obtained from the World Bank website. This study uses various estimates both Pooled OLS (Ordinary Least Square) and Random Effect (RE). However, to overcome the issue of serial correlation which could cause bias in the results of the study, we used fixed-effect (FE) cluster estimates. The research results confirm the previous findings that bank capital positively affects bank stability (natural logarithm of Z-Score) and negatively affects credit risk (loan loss provision to total liabilities). The findings also show that efficiency has the same effect. The interaction test of bank capital and efficiency shows that efficiency encourages banks to reduce risk, including when bank capital is relatively lower. This finding is expected to have implications for the authorities to boost bank efficiency in addition to establishing several regulations related to capital. The efficiency implemented by the bank will encourage banks to act prudently so that the bank can maintain its performance through risk mitigation.