• Communications for Statistical Applications and Methods
• /
• v.14 no.1
• /
• pp.23-32
• /
• 2007

We consider penalized likelihood regression with data from the negative binomial distribution with unknown shape parameter. Smoothing parameter selection and asymptotically efficient low dimensional approximations are employed for negative binomial data along with shape parameter estimation through several different algorithms.

• Corrosion Science and Technology
• /
• v.7 no.5
• /
• pp.296-299
• /
• 2008

High order statistical parameters were evaluated using the electrochemical noise data collected during corrosion of type 430 stainless steel coupled to a inert, platinum electrode in 3.5% NaCl solution. High order statistical parameters are shown to predict uniform corrosion properly. However, Localization index, skewness of current, kurtosis and skewness of potential are capable of predicting pitting corrosion only when the transients are large with long life time. Of the high order statistical parameters evaluated, kurtosis of current is found to be the most sensitive parameter for detecting uniform and pitting corrosion.

• Journal of Applied Reliability
• /
• v.1 no.1
• /
• pp.17-33
• /
• 2001

The characteristics of Weibull distribution are investigated as a function of shape parameter. The statistical estimation methods of the shape parameter and statistical comparison methods of two or more shape parameters are studied. Assuming Weibull distribution, statistical analysis of bending-strength data of alumina titanium carbide ceramic matrix composites machined two different methods are performed.

• Communications for Statistical Applications and Methods
• /
• v.15 no.5
• /
• pp.655-666
• /
• 2008

Small sample likelihood based inference for the shape parameter of the inverse Gaussian distribution is the purpose of this paper. When shape parameter is of interest, the signed log-likelihood ratio statistic and the modified signed log-likelihood ratio statistic are derived. Hsieh (1990) gave a statistical inference for the shape parameter based on an exact method. Throughout simulation, we will compare the statistical properties of the proposed statistics to the statistic given by Hsieh (1990) in term of confidence interval and power of test. We also discuss a real data example.

• Journal of Advanced Research in Ocean Engineering
• /
• v.4 no.4
• /
• pp.185-194
• /
• 2018

In this study, the extreme sloshing pressure was predicted using various statistical models: three-parameter Weibull distribution, generalized Pareto distribution, generalized extreme value distribution, and three-parameter log-logistic distribution. The estimation of sloshing impact pressure is important in design of liquid cargo tank in severe sea state. In order to get the extreme values of local impact pressures, a lot of model tests have been carried out and statistical analysis has been performed. Three-parameter Weibull distribution and generalized Pareto distribution are widely used as the statistical analysis method in sloshing phenomenon, but generalized extreme value distribution and three-parameter log-logistic distribution are added in this study. Additionally, statistical distributions are fitted to peak pressure data using three different parameter estimation methods. The data were obtained from a three-dimensional sloshing model text conducted at Seoul National University. The loading conditions were 20%, 50%, and 95% of tank height, and the analysis was performed based on the measured impact pressure on four significant panels with large sloshing impacts. These fittings were compared by observing probability of exceedance diagrams and probability plot correlation coefficient test for goodness-of-fit.

• Communications for Statistical Applications and Methods
• /
• v.14 no.2
• /
• pp.329-344
• /
• 2007

In this paper, we shall propose the AMLEs of the scale parameter and the location parameter in the two-parameter Rayleigh distribution based on progressive Type-II censored samples when one parameter is known. We also propose the AMLEs of the two parameters in the Rayleigh distribution based on progressive Type-II censored samples when two parameters are unknown. We simulate the mean squared errors of the proposed estimators through Monte Carlo simulation for various censoring schemes.

• Journal of the Korean Statistical Society
• /
• v.26 no.1
• /
• pp.75-88
• /
• 1997

In this paper, a two-parameter version of Ikeda-Watanabe's mollifiers approximation of the Brownian motion is considered, and an approximation theorem corresponding to the one parameter case is proved. Using this approximation, we formulate Wong-Zakai type theorem is a Stochastic Differential Equation (SDE) driven by a two-parameter Wiener process.

• Journal of the Korean Statistical Society
• /
• v.22 no.1
• /
• pp.1-12
• /
• 1993

An approach to make the information bound sharper in median-unbiased estimation, based on an analogue of the Cramer-Rao inequality developed by Sung et al. (1990), is introduced for continuous densities with a nuisance parameter by considering information quantities contained both in the parametric function of interest and in the nuisance parameter in a linear fashion. This approach is comparable to that of improving the information bound in mean-unbiased estimation for the case of two unknown parameters. Computation of an optimal weight corresponding to the nuisance parameter is also considered.

• Proceedings of the Korean Statistical Society Conference
• /
• 2001.11a
• /
• pp.185-189
• /
• 2001

In this paper, we consider the problem of testing for parameter changes in time series models based on a sequential test. Although the test procedure is well-established for the mean and variance change, a general parameter case has not been discussed in the literature. Therefore, we develop a sequential test for parameter changes in a more general framework.

• Communications for Statistical Applications and Methods
• /
• v.10 no.1
• /
• pp.145-151
• /
• 2003

We shall propose several estimators for the scale parameter in the uniform distribution when the parameter is functions of a known exposure level, and obtain expectations and variances for their proposed estimators. And we shall compare numerically relative efficiencies for proposed estimators of the scale parameter in the small sample sizes.