• Journal of the Korean Statistical Society
• /
• v.31 no.3
• /
• pp.379-389
• /
• 2002

For two normal distribution with unknown means and unknown variances, a sequential procedure for estimating the difference of two normal means which satisfies both the coverage probability condition and the $\beta$-protection is proposed under some smoothness of variable imprecision function, and the asymptotic normality of the proposed stopping time after some centering and scaling is given.

• Tunnel and Underground Space
• /
• v.15 no.3 s.56
• /
• pp.228-235
• /
• 2005

Friction angle and cohesion of rock masses can be estimated from Hoek and Brown failure criterion and then plastic corrections can be applied using Mohr-Coulomb yield function. This study finds that this estimation procedure would not be appropriate for weak rock masses and for cases where low confining stress is expected to develop. A procedure is outlined in this paper for estimating plastic corrections directly from Hoek and Brown material model. Comparative study shows that direct procedure would simulate non-linear failure surface better than indirect procedure especially in the low confining stress regime.

• Communications for Statistical Applications and Methods
• /
• v.2 no.2
• /
• pp.63-73
• /
• 1995

We consider some robust Bayes estimators using ML-II priors as well as certain empirical Bayes estimators in estimating the finite population mean. The proposed estimators are compared with the sample mean and subjective Bayes estimators in terms of "posterior robustness" and "procedure robustness".re robustness".uot;.

• Communications for Statistical Applications and Methods
• /
• v.2 no.2
• /
• pp.94-100
• /
• 1995

Vector autoregressive process disturbed by measurement error is a vector autoregressive process with nonlineat parametric restrictions on the parameter. A Newton-Raphson procedure for estimating the parameter which take advantage of the information contained in the restrictions is proposed.

• Proceedings of the Korean Nuclear Society Conference
• /
• 1996.05b
• /
• pp.691-698
• /
• 1996

This paper propose a procedure to estimate the system lifetime distribution using simulation method in a parametric framework and also develop the criterion for terminating the simulation. We assume that a system is composed of many components whose lifetime and repair time distributions are general, and repair of each component is imperfect or not. General simulation algorithms can not be adopted for this case, due to the dependency of successive operating times and the discontinuity in base line intensity function of failure process. Then we propose algorithms for generating failure times subject to imperfect repair. We develop the event time tracking logic for identifying the system failure time, and also develop the criterion for terminating the simulation. Our procedure is composed of two phases. The first phase of the procedure is to generate the system failure times from the inputs. The second phase is to estimate the lifetime distribution of the system. The best model is selected by a fully automated procedure among well-known parametric families, and the required parameters are estimated. We give examples to show the accuracy of our procedure and the effect of repair effect of components to system MTTF(Mean Time To Failure).

• Journal of the Korean Operations Research and Management Science Society
• /
• v.23 no.4
• /
• pp.111-130
• /
• 1998

We propose an imperfect repair model which depends on external effects quantified by covariates. The model is based on the Brown-Proschan imperfect repair model wherefrom the probability of perfect repair is represented by a function of covariates. We are motivated by deficiency of the BP model whose stationarity prevents us from predicting dynamically the time to next failure according to external condition. Five types of function for the probability of perfect repair are proposed. This article also presents a procedure for estimating the parameter of the function for the probability of perfect repair, as well as the inherent lifetime distribution of the system, based on consecutive inter-failure times and the covariates. The estimation procedure is based on the expectation-maximization principle which is suitable to incomplete data problems. focusing on the maximization step, we derive some theorems which guarantee the existence of the solution. A Monte Carlo study is also performed to illustrate the prediction power of the model as well as to show reasonable properties of the estimates. The model reduces significantly the mean square error of the in-sample prediction. so it can be utilized in real fields for evaluating and maintaining repairable systems.

• Journal of the Korean Statistical Society
• /
• v.23 no.2
• /
• pp.325-340
• /
• 1994

Effects of temporal aggregation on estimation for ARMA models are studied by investigating the Hannan & Rissanen (1982)'s procedure. The temporal aggregation of autoregressive process has a representation of an autoregressive moving average. The characteristic polynomials associated with autoregressive part and moving average part tend to have roots close to zero or almost identical. This caused a numerical problem in the Hannan & Rissanen procedure for identifying and estimating the temporally aggregated autoregressive model. A Monte-Carlo simulation is conducted to show the effects of temporal aggregation in predicting one period ahead realization.

• Communications for Statistical Applications and Methods
• /
• v.10 no.3
• /
• pp.1069-1086
• /
• 2003

This article presents the asymptotic theory of triple sampling procedure as pertain to estimating the shape parameter of Pareto distribution. Both point and confidence interval estimation are considered within the same inference unified framework. We show that this group sampling technique possesses the efficiency of Anscome (1953), Chow and Robbins (1965) purely sequential procedure as well as reduce the number of sampling operations by utilizing Stein (1945) two stages procedure. The analysis reveals that the technique performs excellent as far as the accuracy is concerned. The present problem differs from those considered by many authors, in multistage sampling, in that the final stage sample size and the parameter's estimate become highly correlated and therefore we adopted different approach.

• Journal of applied mathematics & informatics
• /
• v.7 no.1
• /
• pp.237-245
• /
• 2000

In this paper, we consider to the adjustment weighting procedure in the two phase sampling scheme. In general, the unit nonresponses may be occured in the final survey operation. When the unit nonresponse be generated in survey, it is able to use the auxiliary variable for estimating of interest variable. In this viewpoint, we use the two kinds level of auxiliary variable, $X_{1k}$ and $X_{2k}$ for the calibration procedure. We proprose the two-step Newton's method in the calibration estimation procedure for the two phase sampling.

• International Journal of Reliability and Applications
• /
• v.4 no.1
• /
• pp.41-50
• /
• 2003

This paper represents the first comprehensive comparison of the Newton-Raphson's method and Simple Iterative Procedure (SIP) in the maximum likelihood estimation of the two-parameter Weibull distribution. Computer simulation is employed to compare these two methods for multiply censored, singly censored data (Type I or Type Ⅱ censoring) and complete data. Results indicate the Newton-Raphson's with the Menon's estimated value, as an initial point remains the effective iterative procedure for estimating the parameters.