• Journal of the Korean Data and Information Science Society
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• 제20권5호
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• pp.933-939
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• 2009

The bivariate data in clinical research fields often has two types of failure times, which are mark variable for the first failure time and the final failure time. This paper showed how to generate bootstrap data to get Bayesian estimation for the joint distribution of bivariate survival times. The observed data was generated by Frank's family and the fake date is simulated with the Gamma prior of survival time. The bootstrap data was obtained by combining the mimic data with the observed data and the simulated fake data from the observed data.

• 한국데이터정보과학회:학술대회논문집
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• 한국데이터정보과학회 2006년도 PROCEEDINGS OF JOINT CONFERENCEOF KDISS AND KDAS
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• pp.327-333
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• 2006

In this paper, we consider the Bayesian hypotheses testing for independence in bivariate exponential model. In Bayesian testing problem, we use the noninformative priors for parameters which are improper and are defined only up to arbitrary constants. And we use the recently proposed hypotheses testing criterion called the fractional Bayes factor. Also we give some numerical results to illustrate our results.

• 대한수학회논문집
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• 제22권2호
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• pp.305-313
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• 2007

Let $A_1,\;A_2,\;\ldots,\;A_m$ and $B_1,\;B_2,\;\ldots,\;B_n$ be two sequences of events on the same probability space. Let $X=X_m(A)\;and\;Y=Y_n(B)$, respectively, denote the numbers of those $A_i's\;and\;B_j's$ which occur. We establish new bivariate Bonferroni-type inequalities using consecutive events and deduce a known result.

• 대한수학회지
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• 제48권5호
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• pp.1065-1081
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• 2011

For any field F, a polynomial f $\in$ F[$x_1,x_2,{\ldots},x_k$] can be associated with a polytope, called its Newton polytope. If the polynomial f has integrally indecomposable Newton polytope, in the sense of Minkowski sum, then it is absolutely irreducible over F, i.e., irreducible over every algebraic extension of F. We present some results giving new integrally indecomposable classes of polygons. Consequently, we have some criteria giving many types of absolutely irreducible bivariate polynomials over arbitrary fields.

• 품질경영학회지
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• 제25권4호
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• pp.79-87
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• 1997

In this paper, we obtain maximum likelihood estimator(MLE) of a parallel system reliability for the Marshall and Olkin's bivariate exponential model with birariate type 1 consored data. The asymptotic normal distribution of the estimator is obtained. Also we construct an a, pp.oximate confidence interval for the reliability based on MLE. We present a numerical study for obtaining MLE and a, pp.oximate confidence interval of the reliability.

• Journal of the Korean Statistical Society
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• 제14권1호
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• pp.7-17
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• 1985

Data set generated by teh bivariate dichotomous choice made by individuals often occurs in practice. This paper presents general model of how such data set is generated as well as methods of estimation. The M.L.E. is examined and found to be computationally burdensome. A simpler estimator, the bivariate dichotomous two-stage estimator, is suggested as an alternative. The two-stage estimator is found to be as efficient as the M.L.E.

• Communications for Statistical Applications and Methods
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• 제6권3호
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• pp.729-748
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• 1999

In this paper we present combined estimator of capture-recapture and line transect model using bivariate detection function and detection probability according to objects being in cluster population. Here bivariate detection function use distance and cluster size. The simulation shows that combined estimator approaches the more true value the larger size parameter. Therefore this estimator using the bivariate detection function is more efficient in estimate the population size and density by size parameter.

• 대한수학회논문집
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• 제21권2호
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• pp.363-374
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• 2006

A new bivariate beta distribution based on the Appell function of the third kind is introduced. Various representations are derived for its product moments, marginal densities, marginal moments, conditional densities and conditional moments. The method of maximum likelihood is used to derive the associated estimation procedure as well as the Fisher information matrix.

• 품질경영학회지
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• 제18권2호
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• pp.101-116
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• 1990

The objectives of this thesis are : first, to estimate the parameters and Pr[X < Y] in the Marshall and Olkin's Bivariate Exponential Distribution ; and secondly, to compare the Bayes estimators of Pr[X < Y] with maximum likelihood estimator of Pr[X < Y] in the Marshall and Olkin's Bivariate Exponential Distribution. Through the Monte Carlo Simulation, we observed that the Bayes estimators of Pr[X < Y] perform better than the maximum likelihood estimator of Pr[X < Y] and the Bayes estimator of Pr[X < Y] with gamma prior distribution performs better than with vague prior distribution with respect to bias and mean squared error in the Marshall and Olkin's Bivariate Exponential Distribution.

• Communications for Statistical Applications and Methods
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• 제12권3호
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• pp.783-795
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• 2005

We consider to obtain an estimate of bivariate survival function for the right censored data with the assumption that the two components of censoring vector are independent. The estimate is derived from an ad hoc approach based on the representation of survival function. Then the resulting estimate can be considered as an extension of the Susarla- Van Ryzin estimate to the bivariate data. Also we show the consistency and weak convergence for the proposed estimate. Finally we compare our estimate with Dabrowska's estimate with an example and discuss some properties of our estimate with brief comment on the extension to the multivariate case.