• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.971-980
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• 2003

The tree method can be extended to multivariate responses, such as repeated measure and longitudinal data, by modifying the split function so as to accommodate multiple responses. Recently, some decision trees for multiple responses have been constructed by Segal (1992) and Zhang (1998). Segal suggested a tree can analyze continuous longitudinal response using Mahalanobis distance for within node homogeneity measures and Zhang suggested a tree can analyze multiple binary responses using generalized entropy criterion which is proportional to maximum likelihood of joint distribution of multiple binary responses. In this paper, we will modify CART procedure and suggest a new tree-based method that can analyze multiple binary responses using similarity measures.

• Communications for Statistical Applications and Methods
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• v.6 no.2
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• pp.443-456
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• 1999

The estimation of mean lifetimes in presence of interval censoring with mixed replacement procedure are examined when the distribution s of lifetimes are exponential. it is assumed that due to physical restrictions and/or economic constraints the number of failures is investigated only at several inspection times during the lifetime test; thus there is interval censoring. Comparisons of mixed replacement designs are made with those with and without replacement The maximum likelihood estimator is found in an implicit form. The Cramer-Rao lower bound which is the asymptotic variance of the estimator is derived. The test conditions for minimizing the Cramer-Rao lower bound and minimizing the test costs within a desired width of the Cramer-Rao bound have been studied.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.6
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• pp.67-74
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• 1995

This paper proposes the step-stress type-I censoring model for analyzing the data of accelerated life test and reducing the time of accelerated life test. In order to obtain the data of accelerated life test, the step-stress accelerated life test was run with voltage stress to CMOS Hex Buffer. The Weibull distribution, the Inverse-power-law model and Maximum likelihood method were used. The iterative procedure using modified-quasi-linearization method is applied to solve the nonlinear equation. The proposed Weibull step-stress type-I censoring model exactly estimases the life time of units, while reducting the time of accelerated life test and the equipments of test.

• Wind and Structures
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• v.31 no.5
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• pp.419-430
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• 2020

Weibull distribution is a conspicuous distribution known for its accuracy and its usage for wind energy analysis. The two and three parameter Weibull distributions are adopted in this study to fit wind speed data. The daily mean wind speed data of Ennore, Tamil Nadu, India has been used to validate the procedure. The parameters are estimated using maximum likelihood method, least square method and moment method. Four statistical tests namely Root mean square error, R2 test, Kolmogorov-Smirnov test and Anderson-Darling test are employed to inspect the fitness of Weibull probability density functions. The value of shape factor, scale factor, wind speed and wind power are determined at a height of 100m using extrapolation of numerical equations. Also, the value of capacity factor is calculated mathematically. This study provides a way to evaluate feasible locations for wind energy assessment, which can be used at any windy site throughout the world.

• Journal of the Korean Statistical Society
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• v.24 no.2
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• pp.481-493
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• 1995

An ARIMA signal observed with measurement error is shown to have another ARIMA representation with nonlinear restrictions on parameters. For this model, the restricted Newton-Raphson estimator(RNRE) of the unit root is shown to have the same limiting distribution as the ordinary least squares estimator of the unit root in an AR(1) model tabulated by Dickey and Fuller (1979). The RNRE of parameters of the ARIMA(p,1,k) process and unit root tests base on the RNRE are developed.

• Communications for Statistical Applications and Methods
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• v.25 no.5
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• pp.523-544
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• 2018

Bivariate distributions play a fundamental role in survival and reliability studies. We consider a regression model for bivariate survival times under right-censored based on the bivariate Kumaraswamy Weibull (Cordeiro et al., Journal of the Franklin Institute, 347, 1399-1429, 2010) distribution to model the dependence of bivariate survival data. We describe some structural properties of the marginal distributions. The method of maximum likelihood and a Bayesian procedure are adopted to estimate the model parameters. We use diagnostic measures based on the local influence and Bayesian case influence diagnostics to detect influential observations in the new model. We also show that the estimates in the bivariate Kumaraswamy Weibull regression model are robust to deal with the presence of outliers in the data. In addition, we use some measures of goodness-of-fit to evaluate the bivariate Kumaraswamy Weibull regression model. The methodology is illustrated by means of a real lifetime data set for kidney patients.

• The Korean Journal of Applied Statistics
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• v.1 no.1
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• pp.39-44
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• 1987

For obtaining the m.l.e. of $\Sigma$ from p-variate Non-singular Normal parent, $N_p(\mu, \Sigma)$, Andersous' Procedure based on the invariance property of the m.l.e. seems to be generally Preferred in the view of its simplicity. This paper shows that his approach with respect to $\Sigma^{-1}$ rather than $\Sigma$ itself, he burther applicable to deriving the m.l.e. of parametersinvolved in the common factor model an dsimplex model as well.

• Structural Engineering and Mechanics
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• v.31 no.5
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• pp.527-544
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• 2009

In this study, the periodic seismic performance evaluation scheme is proposed using a structural health monitoring system in terms of seismic fragility. An instrumented highway bridge is used to demonstrate the evaluation procedure involving (1) measuring ambient vibration of a bridge under general vehicle loadings, (2) identifying modal parameters from the measured acceleration data by applying output-only modal identification method, (3) updating a preliminary finite element model (obtained from structural design drawings) with the identified modal parameters using real-coded genetic algorithm, (4) analyzing nonlinear response time histories of the structure under earthquake excitations, and finally (5) developing fragility curves represented by a log-normal distribution function using maximum likelihood estimation. It is found that the seismic fragility of a highway bridge can be updated using extracted modal parameters and can also be monitored further by utilizing the instrumented structural health monitoring system.

• Communications for Statistical Applications and Methods
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• v.20 no.5
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• pp.347-356
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• 2013

We propose a sequential method to construct approximate confidence limits for the ratio of two independent sequences of binomial variates with unequal sample sizes. Due to the nonexistence of an unbiased estimator for the ratio, we develop the procedure based on a modified maximum likelihood estimator (MLE). We generalize the results of Cho and Govindarajulu (2008) by defining the sample-ratio when sample sizes are not equal. In addition, we investigate the large-sample properties of the proposed estimator and its finite sample behavior through numerical studies, and we make comparisons from the sample information view points.

• Proceedings of the Korea Concrete Institute Conference
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• 2006.11a
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• pp.93-96
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• 2006

This study represents results of performance-based fragility analysis of reinforced concrete (RC) bridge. Monte carlo simulation is performed to study nonlinear dynamic responses of RC bridge. Two-parameter log-normal distribution function is used to represent the fragility curves. These two-parameters, referred to as fragility parameters, are estimated by the traditional maximum likelihood procedure, which. is treated each event of RC bridge pier damage as a realization of Bernoulli experiment. In order to formulate the fragility curves, five different damage states are described by two practical factors: the displacement and curvature ductility, which are mostly influencing on the seismic behavior of RC bridge piers. Five damage states are quantitatively assessed in terms of these seismic ductilities on the basis of numerous experimental results of RC bridge piers. Thereby, the performance-based fragility curves of RC bridge pier are provided in this paper.