• Communications of the Korean Mathematical Society
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• v.14 no.4
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• pp.789-795
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• 1999

Let $A_1$,A$_2$…, A\ulcorner and B$_1$,B$_2$…, B\ulcorner be two sequences of events on the same probability space. Let X= X\ulcorner(A) and Y-Y\ulcorner)(B), repectively, by the number of those A\ulcorner and B\ulcorner which oc-cur. We establish bivariate lower bounds on the distribution P(X$\geq$1, Y, $\geq$1)and P(X$\geq$i , $Y\geq$j)by linear combinations of the bino-mial moments S\ulcorner, \ulcorner, 1$\leq$i$\leq$j

• The Korean Journal of Applied Statistics
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• v.25 no.5
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• pp.775-783
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• 2012

Several statistical models for bivariate poisson data are suggested and used to analyze 2011 K-league data. Our interest is composed of two purposes: The first purpose is to exploit potential attacking and defensive abilities of each team. Particular, a bivariate poisson model with diagonal inflation is incorporated for the estimation of draws. A joint model is applied to estimate an association between poisson distribution and probability of draw. The second one is to investigate causes on scoring time of goals and a regression technique of recurrent event data is applied. Some related future works are suggested.

• Journal of the Korean Data and Information Science Society
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• v.23 no.4
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• pp.851-858
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• 2012

We consider a bivariate Poisson regression model to analyze discrete count data when two dependent variables are present. We estimate the regression coefficients as sociated with several safety countermeasures. We use Markov chain and Monte Carlo techniques to execute some computations. A simulation and real data analysis are performed to demonstrate model fitting performances of the proposed model.

• Communications for Statistical Applications and Methods
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• v.18 no.5
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• pp.571-579
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• 2011

We propose a new bivariate zero-inflated negative binomial regression model to allow heterogeneous dispersions. To show the performance of our proposed model, Health Care data in Deb and Trivedi (1997) are used to compare it with the other bivariate zero-inflated negative binomial model proposed by Wang (2003) that has a common dispersion between the two response variables. This empirical study shows better results from the views of log-likelihood and AIC.

• The Korean Journal of Applied Statistics
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• v.5 no.2
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• pp.193-209
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• 1992

We consider a Step Life Testing which is deviced for a two-component serial system with the considerably long life time. In the modelling stage we discuss the bivariate exponential distribution suggested by Block and Basu as the bivariate survival function for the two-component system, and develope the cumulative exposure model introduced by Nelson so that it can be used under the bivariate function. We consider inference on the component life time when the components are at work in the system by combining the information from system life test and that from the component tests carried out separately under the controlled environment. In data analysis, maximum likelihood estimators are discussed with the initial value obtained by an weighted least square method. Finally we discuss the optimal time for changing the stress in the simple step stress life testing.

• Journal of the Korean Data and Information Science Society
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• v.27 no.3
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• pp.711-724
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• 2016

Under variable complex operating environment, various factors can affect the lifetimes of systems. In this research, we study bivariate reliability models having multiple dynamic competing risks. As competing risks, in addition to the natural failure, we consider the increased stress caused by the failure of one component, external shocks, and the level of stress of the working environment at the same time. Considering two reliability models which take into account all of these competing risks, we derive bivariate life distributions. Furthermore, we compare these two models and also compare the distributions of maximum and minimum statistics in the two models.

• Journal of the Korean Society of Hazard Mitigation
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• v.11 no.2
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• pp.137-146
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• 2011

In this study, annual maximum storm events are evaluated by applying the bivariate extremal distribution. Rainfall quantiles of probabilistic storm event are calculated using OR case joint return period, AND case joint return period and interval conditional joint return period. The difference between each of three joint return periods was explained by the quadrant which shows probability calculation concept in the bivariate frequency analysis. Rainfall quantiles under AND case joint return periods are similar to rainfall depths in the univariate frequency analysis. The probabilistic storm events overcome the primary limitation of conventional univariate frequency analysis. The application of these storm event analysis provides a simple, statistically efficient means of characterizing frequency of extreme storm event.

• Journal of Korea Water Resources Association
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• v.47 no.2
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• pp.171-182
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• 2014

The objective of this study is to evaluate the utilization of bivariate joint drought index in South Korea. In order to develop the bivariate joint drought index, in this study, Clayton copula was used to estimate the joint distribution function and the calibration method was employed for parameter estimation. Precipitation and soil moisture data were selected as input data of bivariate joint drought index for period of 1977~2012. The time series analysis, ROC (Receiver Operating Characteristic) analysis, spatial analysis were used to evaluate the bivariate joint drought index with SPI (Standardized Precipitation Index) and SSI (Standardized Soil moisture Index). As a result, SPI performed better for drought onset and SSI for drought demise. On the other hand the bivariate joint drought index captured both drought onset and demise very well. The ROC score of bivariate joint drought index was higher than that of SPI and SSI, and it also reflected the local drought situations. The bivariate joint drought index overcomes the limitations of existing drought indices and is useful for drought analysis.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.235-242
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• 2002

In this paper, we develop noninformative priors that are used for estimating the ratio of failure rates under Freund's bivariate exponential distribution. A class of priors is found by matching the coverage probabilities of one-sided Baysian credible interval with the corresponding frequentist coverage probabilities. Also the propriety of posterior under the noninformative priors is proved and the frequentist coverage probabilities are investigated for small samples via simulation study.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.243-250
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• 2002

This paper considers the problem of estimating parameters of the bivariate exponential distribution with a location parameter for a two-component shared parallel system using component data from system-level life test terminated at the time of the prespecified number of system failure. In the system-level life testing, there are three patterns of failure types ; 1) both component failed 2) both component censored 3) one is failed and the other is censored. In the third case, we assume that the failure time might be known or unknown. The maximum likelihood estimators are obtained for the case of known/unknown failure time when the other component is censored.