• Communications for Statistical Applications and Methods
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• 제18권2호
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• pp.245-255
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• 2011

자료의 분포변화를 검정하는 비모수적 방법으로 경험분포함수를 이용하거나 확률밀도함수 추정량을 이용하는 두 가지 방법을 고려할 수 있다. 이 논문에서는 분포변화 검정을 위한 두가지 방법을 자세히 살펴보고 기존 연구의 결과를 정리한다. 여러 확률모형을 가정하고 분포변화 검정에 대한 모의 실험을 실시하여 두 방법에 대한 이론적 극한 성질이잘 성립하는가를 살펴본다. 검정력 비교를 통하여 모형에 따른 적절한 변화점 분석 방법을 알아본다.

• 유통과학연구
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• 제20권6호
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• pp.43-56
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• 2022

Purpose: This study aims to investigate the impact of investing into technology development on banking performance in an emerging country. Research design, data and methodology: Based on the data of 12 commercial banks listed in Vietnam from 2011 to 2019 and performing multivariable regression analyses as well as conducting a variety of robustness tests, we carry out the empirical investigation to discover this impact. Results: Our empirical evidence shows that these spending help to improve significantly performance of banks. Particularly, the technology expenditures have positive effect on the net interest margin and the non-interest income in which the level of influence on the latter is relatively remarkable in comparison with the former. At the same time, the result does not support the view that increasingly spending on technology may lead banks to face the risk of instability. Conclusions: Overall, our empirical analysis indicates that increasing investment into distribution information and communication technologies will help to enhance business strategies of banks and thus we advocate the bright side of technology development and digitalization in banking sector. We believe that the research is useful for both managers, regulators and policy makers in Vietnam as well as in countries having similar financial structure.

• Journal of the Korean Statistical Society
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• 제30권3호
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• pp.481-498
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• 2001

Empirical Bayes procedure of nonparametric estiamtion of cumulative hazard rates based on censored data is considered using the beta process priors of Hjort(1990). Beta process priors with unknown parameters are used for cumulative hazard rates. Empirical Bayes estimators are suggested and asymptotic optimality is proved. Our result generalizes that of Susarla and Van Ryzin(1978) in the sensor that (i) the cumulative hazard rate induced by a Dirichlet process is a beta process, (ii) our empirical Bayes estimator does not depend on the censoring distribution while that of Susarla and Van Ryzin(1978) does, (iii) a class of estimators of the hyperprameters is suggested in the prior distribution which is assumed known in advance in Susarla and Van Ryzin(1978). This extension makes the proposed empirical Bayes procedure more applicable to real dta sets.

• Communications for Statistical Applications and Methods
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• 제15권2호
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• pp.213-228
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• 2008

Using a linear loss function, this paper considers the one-sided testing problem for the exponential distribution via the empirical Bayes(EB) approach. Based on right censored data, we propose an EB test for the exponential parameter and obtain its convergence rate and asymptotic optimality, firstly, under the condition that the censoring distribution is known and secondly, that it is unknown.

• Communications for Statistical Applications and Methods
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• 제14권1호
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• pp.71-80
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• 2007

The present paper investigates estimation of a scale parameter of a gamma distribution using a loss function that reflects both goodness of fit and precision of estimation. The Bayes and empirical Bayes estimators rotative to balanced loss functions (BLFs) are derived and optimality of some estimators are studied.

• Journal of the Korean Data and Information Science Society
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• 제8권2호
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• pp.261-270
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• 1997

This paper is proposed the parametric empirical Bayes(EB) confidence intervals which corrects the deficiencies in the naive EB confidence intervals of the scale parameter in the Weibull distribution under item-censoring scheme. In this case, the bootstrap EB confidence intervals are obtained by the parametric bootstrap introduced by Laird and Louis(1987). The comparisons among the bootstrap and the naive EB confidence intervals through Monte Carlo study are also presented.

• 대한수학회지
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• 제47권6호
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• pp.1137-1146
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• 2010

In this paper, we study the divergence based goodness of fit test for partially observed sample from diffusion processes. In order to derive the limiting distribution of the test, we study the asymptotic behavior of the residual empirical process based on the observed sample. It is shown that the residual empirical process converges weakly to a Brownian bridge and the associated phi-divergence test has a chi-square limiting null distribution.

• 응용통계연구
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• 제6권1호
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• pp.173-181
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• 1993

각 성분 문제에서, 표본의 크기가 상이한 경우 Dirichlet process prior에 대한 경험적 베이 즈에 대한 분포함수의 추정문제를 연구하였다. 특히, 위의 경험적 베이즈 문제에 사용할 수 있도록 Zehnwirth의 $\alpha(R)$을 수정하였다.

• Communications for Statistical Applications and Methods
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• 제8권1호
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• pp.291-297
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• 2001

For a stochastic regression model in which the errors are assumed to form a stationary linear process, we show that the difference between the empirical distribution functions of the errors and the estimates of those errors converges uniformly in probability to zero at the rate of $o_{p}$ ( $n^{-}$$\frac{1}{2}$) as the sample size n increases.

• Communications for Statistical Applications and Methods
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• 제21권6호
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• pp.539-559
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• 2014

We derive the exact distribution of summation for random samples from uniform distribution and then compare the exact distribution with the approximated normal distribution obtained by the central limit theorem. To check the similarity between two distributions, we consider five existing normality tests based on the difference between the target normal distribution and empirical distribution: Anderson-Darling test, Kolmogorov-Smirnov test, Cramer-von Mises test, Shapiro-Wilk test and Shaprio-Francia test. For the purpose of comparison, those normality tests are applied to the simulated data. It can sometimes be difficult to derive an exact distribution. Thus, we try two different transformations to find out which transform is easier to get the exact distribution in terms of calculation complexity. We compare two transformations and comment on the advantages and disadvantages for each transformation.