• Journal of the Korean Statistical Society
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• v.34 no.3
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• pp.235-244
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• 2005

In recent years, theoretical properties of Bayesian nonparametric survival models have been studied and the conclusion is that although there are pathological cases the popular prior processes have the desired asymptotic properties, namely, the posterior consistency and the Bernstein-von Mises theorem. In this study, through a simulation experiment, we study the finite sample properties of the Bayes estimator and compare it with the frequentist estimators. To our surprise, we conclude that in most situations except that the prior is highly concentrated at the true parameter value, the Bayes estimator performs worse than the frequentist estimators.

• Proceedings of the Korean Statistical Society Conference
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• 2002.11a
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• pp.115-117
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• 2002

In this paper, we obtain an explicit formula of the Laplace transform of the forward recurrence time at finite time t > 0 in an alternating renewal process, by adopting a Markovian approach. As a consequence, we obtain the first two moments of the forward recurrence time.

• Journal of the Korean Statistical Society
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• v.18 no.2
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• pp.135-148
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• 1989

Cumulative sum schemes based on a weighted score are considered for controlling the mean of a continuous production process; in which both the one-sided and two-sided schemes are proposed. The average run lengths and the run length distributions for the proposed schemes are obtained by the Markov chain approach. Comparisons by the average run length show that the proposed schemes perform nearly as well as the standard cumulative sum schemes in detecting changes in the process mean. Comparisons of the one-sided schemes by the run length distribution are also presented.

• Communications for Statistical Applications and Methods
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• v.19 no.5
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• pp.743-750
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• 2012

In this study, we propose definitions for the one-sided variance for asymmetric distribution. We consider to apply the one-sided variance to the construction to define modified $C_{pk}$, which is a definition for the process capability index for the asymmetric process distribution. Then we consider to obtain the consistent estimation for the one-sided variance and to apply to the various industrial fields.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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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.

• Journal of the Korean Statistical Society
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• v.28 no.1
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• pp.45-55
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• 1999

Knowing the number of unit roots is important in the analysis of k-dimensional multivariate autoregressive process. In this paper we suggest simple multiple unit roots test statistics based on least squares estimator for the multivariate AR(1) process in which some eigenvalues are one and the rest are less than one in magnitude. The empirical distributions are tabulated for suggested test statistics. We have small Monte-Calro studies to compare the powers of the test statistics suggested by Johansen(1988) and in this paper.

• Journal of the Korean Statistical Society
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• v.31 no.1
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• pp.17-31
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• 2002

This paper considers noninformative priors for the power law process under failure truncation. Jeffreys'priors as well as reference priors are found when one or both parameters are of interest. These priors are compared in the light of how accurately the coverage probabilities of Bayesian credible intervals match the corresponding frequentist coverage probabilities. It is found that the reference priors have a definite edge over Jeffreys'prior in this respect.

• Journal of the Korean Statistical Society
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• v.26 no.2
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• pp.155-170
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• 1997

We propose an integer-valued MA(q) process with Poisson disturbance. Its various properties are discussed such as the joint distribution, time reversibility and regression. We derive the asymptotic distribution of autocovariance function and estimators of the parameters in the suggested model. We also consider the relationship between INMA(q) and M/D/.infty. processes.

• Journal of the Korean Statistical Society
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• v.33 no.4
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• pp.353-365
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• 2004

In this paper, we define the weighted U-empirical process for simple linear model and show the weak convergence to a Gaussian process under some conditions. Then we illustrate the usage of our result with examples. In the appendix, we derive the variance of the weighted U-empirical distribution function.

• Journal of the Korean Statistical Society
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• v.34 no.4
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• pp.281-295
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• 2005

We investigate the rate of convergence of the distribution of the maximum likelihood estimator (MLE) of an unknown parameter in the drift coefficient of a stochastic process described by a linear stochastic differential equation driven by a fractional Brownian motion (fBm). As a special case, we obtain the rate of convergence for the case of the fractional Ornstein- Uhlenbeck type process studied recently by Kleptsyna and Le Breton (2002).