• Communications for Statistical Applications and Methods
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• v.26 no.2
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• pp.205-216
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• 2019

Diagnostic tests in medical fields detect or diagnose a disease with results measured by continuous or discrete ordinal data. The performance of a diagnostic test is summarized using the receiver operating characteristic (ROC) curve and the area under the curve (AUC). The diagnostic test is considered clinically useful if the outcomes in actually-positive cases are higher than actually-negative cases and the ROC curve is concave. In this study, we apply the stochastic ordering method in a Bayesian hierarchical model to estimate the proper ROC curve and AUC when the diagnostic test results are measured in discrete ordinal data. We compare the conventional binormal model and binormal model under stochastic ordering. The simulation results and real data analysis for breast cancer indicate that the binormal model under stochastic ordering can be used to estimate the proper ROC curve with a small bias even though the sample sizes were small or the sample size of actually-negative cases varied from actually-positive cases. Therefore, it is appropriate to consider the binormal model under stochastic ordering in the presence of large differences for a sample size between actually-negative and actually-positive groups.

• Journal of applied mathematics & informatics
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• v.35 no.5_6
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• pp.543-550
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• 2017

In this paper, we introduced a new asymptotic pairwise negatively dependent(APND) structure of stochastic processes. We are also important to know the degree of APND-ness and to compare pairs of stochastic vectors as to their APND-ness. So, we introduced a definitions and some basic properties of APND ordering. Some preservation results of APND ordering are derived. Finally, we shown some examples and applications.

• Journal of applied mathematics & informatics
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• v.5 no.2
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• pp.553-564
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• 1998

In this paper we introduce a new concept of more weakly quadrant dependence of hitting times of stochastic processes. This concept is weaker than the more positively quadrant dependence of hitting times of stochastic processes. This concept is weaker than the more positively quadrant dependence and it is closed under some statistical operations of weakly positive quadrant dependence(WPQD) ordering.

• Communications for Statistical Applications and Methods
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• v.16 no.6
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• pp.1023-1029
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• 2009

Oh (2009) has proposed a likelihood ratio test for comparing two agreements for dependent observations based on the concept of marginal homogeneity and marginal stochastic ordering. In this paper we consider the comparison of more than two agreement measures. Simple ordering and simple tree ordering among agreement measures are investigated. Some test procedures, including likelihood ratio test, are discussed.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1987.10a
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• pp.35-35
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• 1987

Consider a job shop that is modelled as an open queueing network of the Jackson(l957) type. All work stations in the shop have the same number of parallel servers. Two problems are studied : the loading of stations and the assignment of servers, which are represented by loading and assingment vectors, respectively. Ma jorization and arrangement orderings are established to order, respectively, the loading and the assignment vectors. It is shown that reducing the loading vector under ma jorizat ion or increasing the assignment vector under arrangement ordering will reduce the congestion in the shop in terms of reducing the total number of jobs(in the sense of likelihood ratio ordering), the maximum queue length(in the sense of stochastic ordering), and the queue-length vector( in the sense of stochastic majorization). The results can be used to supprot production planning in certain job shops, and to aid the desing of storage capacity. (OPEN QUEUEING NETWORK; WJORIZATION; ARRANGEMENT ORDERINC; LIKELIHOOD RATIO ORDERINC; STOCHASTIC ORDERING)

• Journal of the Korean Data and Information Science Society
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• v.14 no.2
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• pp.413-428
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• 2003

If a restriction is imposed only to a (proper) subset of parameters of interest, we call it a local restriction. Statistical inference under a local restriction in multinomial setting is studied. The maximum likelihood estimation under a local restriction and likelihood ratio tests for and against a local restriction are discussed. A real data is analyzed for illustrative purpose.

• Journal of the Korean Data and Information Science Society
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• v.15 no.1
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• pp.201-210
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• 2004

The peakedness ordering is closely related to dispersive ordering. In this paper we consider the statistical inference concerning peakedness ordering between two arbitrary symmetric distributions. Nonparametric maximum likelihood estimates of two distribution functions under symmetry and peakedness ordering are given. The likelihood ratio test for equality of two symmetric discrete distributions in the sense of peakedness ordering is studied.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.4
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• pp.1-10
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• 2004

In this paper we study bounds for characteristics of stationary waiting times in (max, +)-linear systems with a Poisson arrival process. which are prevalent in manufacturing systems, kanban systems, cyclic and acyclic fork-and-join type systems, finite or infinite capacity tandem queues with various kinds of blocking, transportation systems, and telecommunication networks, and so on. Recently, some results on series expansion for characteristics, such as higher moments, Laplace transform, and tail probability, of transient and stationary waiting times in a class of (max, +)-linear systems via Taylor series expansions have been studied. In order to overcome the computational complexity in those results, we consider bounds for characteristics of stationary waiting times using valuable stochastic ordering results. Some numerical examples are also provided.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.109-114
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• 2003

The concept of dispersion is intrinsic to the theory and practice of statistics. A formulation of the concept of dispersion can be obtained by comparing the probability of intervals centered about a location parameter, which is peakedness ordering introduced first by Birnbaum (1948). We consider statistical inference concerning peakedness ordering between two arbitrary distributions. We propose nonparametric maximum likelihood estimator of two distributions under peakedness ordering and a likelihood ratio test for equality of dispersion in the sense of peakedness ordering.

• Journal of the Korean Statistical Society
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• v.33 no.3
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• pp.303-312
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• 2004

The concept of dispersion is intrinsic to the theory and practice of statistics. A formulation of the concept of dispersion can be obtained by comparing the probability of intervals centered about a location parameter. This is the peakedness ordering introduced first by Birnbaum (1948). We consider statistical inference concerning peakedness ordering between two arbitrary distributions. We propose non parametric maximum likelihood estimators of two distributions under peakedness ordering and a likelihood ratio test for equality of dispersion in the sense of peakedness ordering.