• Title/Summary/Keyword: Associate

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Expected Number of Visits of the Regenerative Process (재생프로세스에서 기대방문횟수에 대한 연구)

  • 심동희
    • Journal of the Korean Operations Research and Management Science Society
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    • v.25 no.3
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    • pp.35-39
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    • 2000
  • Expected number of visits in the steady state of the regenerative process is one of the most useful characteristics. The formula for this expected number of visits in the steady state of the regenerative process is presented in this paper. Because this formula is for the general model, it can be applied to many special systems including 2-unit redundant system. An example for this formula is also presented.

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CONSTRUCTION OF SOME PROCESSES ON THE WIENER SPACE ASSOCIATED TO SECOND ORDER OPERATORS

  • Cruzeiro, A.B.
    • Journal of the Korean Mathematical Society
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    • v.38 no.2
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    • pp.311-319
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    • 2001
  • We show that it is possible to associate diffusion processes to second order perturbations of the Ornstein-Uhlenbeck operator L on the Wiener space of the form L = L + 1/2∑L$^2$(sub)ξ(sub)$\kappa$ where the ξ(sub)$\kappa$ are "tangent processes" (i.e., semimartingales with antisymmetric diffusion coefficients).

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RIBAUCOUR TRANSFORMATIONS OF THE SURFACES WITH CONSTANT POSITIVE GAUSSIAN CURVATURES IN THE 3-DIMENSIONAL EUCLIDEAN SPACE

  • PARK, Joon-Sang
    • Communications of the Korean Mathematical Society
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    • v.21 no.1
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    • pp.165-175
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    • 2006
  • We associate the surfaces of constant Gaussian curvature K = 1 with no umbilics to a subclass of the solutions of $O(4,\;1)/O(3){\times}O(1,\;1)-system$. From this correspondence, we can construct new K = 1 surfaces from a known K = 1 surface by using a kind of dressing actions on the solutions of this system.

Bayes Prediction Density in Linear Models

  • Kim, S.H.
    • Communications for Statistical Applications and Methods
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    • v.8 no.3
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    • pp.797-803
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    • 2001
  • This paper obtained Bayes prediction density for the spatial linear model with non-informative prior. It showed the results that predictive inferences is completely unaffected by departures from the normality assumption in the direction of the elliptical family and the structure of prediction density is unchanged by more than one additional future observations.

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A Decision Tree-based Analysis for Paralysis Disease Data

  • Shin, Yangkyu
    • Communications for Statistical Applications and Methods
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    • v.8 no.3
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    • pp.823-829
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    • 2001
  • Even though a rapid development of modem medical science, paralysis disease is a highly dangerous and murderous disease. Shin et al. (1978) constructed the diagnosis expert system which identify a type of the paralysis disease from symptoms of a paralysis disease patients by using the canonical discriminant analysis. The decision tree-based analysis, however, has advantages over the method used in Shin et al. (1998), such as it does not need assumptions - linearity and normality, and suggest appropriate diagnosis procedure which is easily explained. In this paper, we applied the decision tree to construct the model which Identify a type of the paralysis disease.

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Preference Map using Weighted Regression

  • S.Y. Hwang;Jung, Su-Jin;Kim, Young-Won
    • Communications for Statistical Applications and Methods
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    • v.8 no.3
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    • pp.651-659
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    • 2001
  • Preference map is a widely used graphical method for the preference data set which is frequently encountered in the field of marketing research. This provides joint configuration usually in two dimensional space between "products" and their "attributes". Whereas the classical preference map adopts the ordinary least squares method in deriving map, the present article suggests the weighted least squares approach providing the better graphical display and interpretation compared to the classical one. Internet search engine data in Korea are analysed for illustration.

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Comparative Study of Confidence Intervals for Relative Ratio

  • Park, Sang-Gue;Oh, You-Jin
    • Communications for Statistical Applications and Methods
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    • v.6 no.2
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    • pp.621-634
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    • 1999
  • Consider the several methods of constructing interval for relative ration from two independent binomial samples. The special interests are gives in the cases of low rates and small samples. bias-corrected and accelerated bootstrap method is proposed to overcome are the non-efficiency of current methods based on asymptotic resuts. Simulation studies are presented to demonstrate the performance of the proposed method.

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Sensitivity Analysis for Ordered Categorical Data

  • Cho, Il-Hyun;Park, Taesung
    • Communications for Statistical Applications and Methods
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    • v.6 no.2
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    • pp.375-382
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    • 1999
  • Linear-by-linear association models are commonly used to analyze ordered categorical data. To fit these models appropriate scores need to be chosen. In this paper we perform sensitivity analyses in two-way contingency tables to investigate the effect of scores on goodness-of-fits and on tests of significance. In addition we show that the best score which yields the best fit of data can be selected based on the sensitivity analysis results.

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Evaluating Predictive Ability of Classification Models with Ordered Multiple Categories

  • Oong-Hyun Sung
    • Communications for Statistical Applications and Methods
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    • v.6 no.2
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    • pp.383-395
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    • 1999
  • This study is concerned with the evaluation of predictive ability of classification models with ordered multiple categories. If categories can be ordered or ranked the spread of misclassification should be considered to evaluate the performance of the classification models using loss rate since the apparent error rate can not measure the spread of misclassification. Since loss rate is known to underestimate the true loss rate the bootstrap method were used to estimate the true loss rate. thus this study suggests the method to evaluate the predictive power of the classification models using loss rate and the bootstrap estimate of the true loss rate.

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