• Title/Summary/Keyword: statistical comparison

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Comparison of Confidence Subsets for Umbrella Orderings

  • Dong Hee Kim;Young Cheol Kim
    • Communications for Statistical Applications and Methods
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    • v.4 no.2
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    • pp.421-426
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    • 1997
  • This paper proposes a distribution-free procedure that obtain confidence subset for umbrella orderings. We compare the proposed confidence procedure with Pan's(1996) confidence procedure.

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On Some Properties of Amount of Information

  • Kim, Jae-Joo;Suh, Kil-Won
    • Journal of the Korean Statistical Society
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    • v.4 no.2
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    • pp.97-109
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    • 1975
  • To gain knowledge about the unknown state $\theta$ of nature, we perform experiments. Sufficiency of an experiment for another experiment has been introduced for the comparison of experiments. The knoledge before and after an experiment makes it possible to discuss the amount of information provided by the experiment.

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Asymptotic Comparison of Latin Hypercube Sampling and Its Stratified Version

  • Lee, Jooho
    • Journal of the Korean Statistical Society
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    • v.28 no.2
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    • pp.135-150
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    • 1999
  • Latin hypercube sampling(LHS) introduced by McKay et al. (1979) is a widely used method for Monte Carlo integration. Stratified Latin hypercube sampling(SLHS) proposed by Choi and Lee(1993) improves LHS by combining it with stratified sampling. In this article it is shown that SLHS yields an asymptotically more accurate than both stratified sampling and LHS.

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Comparison of Perturbation Analysis Estimate and Forward Difference Estimate in a Markov Renewal Process

  • Park, Heung-sik
    • Communications for Statistical Applications and Methods
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    • v.7 no.3
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    • pp.871-884
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    • 2000
  • Using simulation, we compare the perturbation analysis estimate and the forward difference estimate for the first and second derivatives of performance measures in a Markov renewal process. We find the perturbation analysis estimate has much les mean squared error than the traditional forward difference estimate.

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On the Bias of Bootstrap Model Selection Criteria

  • Kee-Won Lee;Songyong Sim
    • Journal of the Korean Statistical Society
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    • v.25 no.2
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    • pp.195-203
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    • 1996
  • A bootstrap method is used to correct the apparent downward bias of a naive plug-in bootstrap model selection criterion, which is shown to enjoy a high degree of accuracy. Comparison of bootstrap method with the asymptotic method is made through an illustrative example.

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A Comparison of Variance Lower Bound between the Optimum Allocation and the Power Allocation

  • Son, Chang-Kyoon
    • Communications for Statistical Applications and Methods
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    • v.10 no.1
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    • pp.79-88
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    • 2003
  • In this paper, we study the efficiency of the stratified estimator in related with the variance lower bound of Horvitz-Thompson estimator subject to the superpopulation model. Especially, we compare the variance lower bound of optimum allocation with that of power allocation subject to Dalenius-Hedges stratification.

Change-point Estimation with Loess of Means

  • Kim, Jae-Hee
    • Communications for Statistical Applications and Methods
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    • v.12 no.2
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    • pp.349-357
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    • 2005
  • We suggest a functional technique with loess smoothing for estimating the change-point when there is one change-point in the mean model. The proposed change-point estimator is consistent. Simulation study shows a good performance of the proposed change-point estimator in comparison with other parametric or nonparametric change-point estimators.

Statistical tests for biosimilarity based on relative distance between follow-on biologics for ordinal endpoints

  • Yoo, Myung Soo;Kim, Donguk
    • Communications for Statistical Applications and Methods
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    • v.27 no.1
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    • pp.1-14
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    • 2020
  • Investigations of biosimilarity between reference drugs and test drugs required statistical tests; in addition, statistical tests to evaluate biosimilarity have been recently proposed. Ordinal outcome data has been observed in research; however, appropriate statistical tests to deal with ordinal endpoints for biosimilar have not yet been proposed. This paper extends existing design for ordinal endpoints. Using measure of nominal-ordinal association and relative distances between drugs are defined so that testing procedures are developed. Through simulation studies, we investigate type I error rate and power to show the performance of our suggested method. Furthermore, a comparison between the statistical tests and other designs is proviede to show significance of ordinal endpoints.

Development of a Simplified Statistical Methodology for Nuclear Fuel Rod Internal Pressure Calculation

  • Kim, Kyu-Tae;Kim, Oh-Hwan
    • Nuclear Engineering and Technology
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    • v.31 no.3
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    • pp.257-266
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    • 1999
  • A simplified statistical methodology is developed in order to both reduce over-conservatism of deterministic methodologies employed for PWR fuel rod internal pressure (RIP) calculation and simplify the complicated calculation procedure of the widely used statistical methodology which employs the response surface method and Monte Carlo simulation. The simplified statistical methodology employs the system moment method with a deterministic approach in determining the maximum variance of RIP The maximum RIP variance is determined with the square sum of each maximum value of a mean RIP value times a RIP sensitivity factor for all input variables considered. This approach makes this simplified statistical methodology much more efficient in the routine reload core design analysis since it eliminates the numerous calculations required for the power history-dependent RIP variance determination. This simplified statistical methodology is shown to be more conservative in generating RIP distribution than the widely used statistical methodology. Comparison of the significances of each input variable to RIP indicates that fission gas release model is the most significant input variable.

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