• Title/Summary/Keyword: Calibration Factor

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Default Bayesian testing for the bivariate normal correlation coefficient

  • Kang, Sang-Gil;Kim, Dal-Ho;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.5
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    • pp.1007-1016
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    • 2011
  • This article deals with the problem of testing for the correlation coefficient in the bivariate normal distribution. We propose Bayesian hypothesis testing procedures for the bivariate normal correlation coefficient under the noninformative prior. The noninformative priors are usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. So we propose the default Bayesian hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. A simulation study and an example are provided.

Default Bayesian testing for the equality of the scale parameters of several inverted exponential distributions

  • Kang, Sang Gil;Kim, Dal Ho;Lee, Woo Dong
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.4
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    • pp.961-970
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    • 2014
  • This article deals with the problem of testing the equality of the scale parameters of several inverted exponential distributions. We propose Bayesian hypothesis testing procedures for the equality of the scale parameters under the noninformative prior. The noninformative prior is usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. So we propose the default Bayesian hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. Simulation study and an example are provided.

Validation of Korean Version of Multidimensional Students' Life Satisfaction Scale (한국판 아동용 다면적 생활만족도 척도(K-MSLSS)의 타당화 연구)

  • Lee, Jeong Mi;Lee, Yanghee
    • Korean Journal of Child Studies
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    • v.29 no.4
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    • pp.249-268
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    • 2008
  • The Korean version of the Multidimensional Students' Life Satisfaction Scale for children(K-MSLSS) assesses children's subjective perceptions of Life Satisfaction(LS) in five conceptually relevant domains : Friends, School, Family, Living Environment, and Self. The purpose of the present study was to validate the five-factor structure of the K-MSLSS using Confirmatory Factor Analysis(CFA) procedures by means of the AMOS 7.0 statistical program. Of the 681 children(10.5 years, SD=1.1) recruited from three public elementary schools in Seoul 431 children were the calibration sample and 430 children were the validation sample. Results of the analyses found that the five-factor structure of K-MSLSS is applicable for use with Korean children from 9-12 years of age regardless of gender.

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Default Bayesian hypothesis testing for the scale parameters in nonregular Pareto distributions

  • Kang, Sang Gil
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.6
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    • pp.1299-1308
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    • 2012
  • This article deals with the problem of testing the equality of the scale parameters in nonregular Pareto distributions.We propose Bayesian hypothesis testing procedures for the equality of the scale parameters under the noninformative prior. The noninformative prior is usually improper which yields a calibration problem that makes the Bayes factor to be de ned up to a multiplicative constant. So we propose the default Bayesia hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. Simulation study and a real data example are provided.

Default Bayesian testing equality of scale parameters in several inverse Gaussian distributions

  • Kang, Sang Gil;Kim, Dal Ho;Lee, Woo Dong
    • Journal of the Korean Data and Information Science Society
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    • v.26 no.3
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    • pp.739-748
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    • 2015
  • This paper deals with the problem of testing about the equality of the scale parameters in several inverse Gaussian distributions. We propose default Bayesian testing procedures for the equality of the shape parameters under the reference priors. The reference prior is usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. Therefore we propose the default Bayesian testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. Simulation study and an example are provided.

Effect of C Factor Errors on the Analysis of Water Distribution Systems (C계수의 추정오차가 배수관망해석에 미치는 영향)

  • Hyun, In Hwan;Lee, Cheol Kyu
    • Journal of Korean Society of Water and Wastewater
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    • v.13 no.2
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    • pp.23-33
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    • 1999
  • This study is to investigate the effect of C factor errors on the analysis of water distribution systems. For this purpose, an artificial distribution network and a real distribution network were selected as the study networks. Results are as follows. 1. The C factor of a pipe which has small velocity didn't give significant effect on the analysis of a water distribution system. 2. The effect of decreased value of C factors give more influence on the analysis of water distribution systems than that of the increased values. 3. For the C factor calibration, errors of the residual water heads as well as those of the head losses should be considered together. 4. In the analysis of water distribution systems, changes of C factors can give influences only on the nodes which locate behind the pipe. Therefore, this characteristics should be considered in the selection of nodes for the measurement of water heads.

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Default Bayesian hypothesis testing for the scale parameters in the half logistic distributions

  • Kang, Sang Gil;Kim, Dal Ho;Lee, Woo Dong
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.2
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    • pp.465-472
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    • 2014
  • This article deals with the problem of testing the equality of the scale parameters in the half logistic distributions. We propose Bayesian hypothesis testing procedures for the equality of the scale parameters under the noninformative priors. The noninformative prior is usually improper which yields a calibration problem that makes the Bayes factor to be dened up to a multiplicative constant. Thus we propose the default Bayesian hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. Simulation study and an example are provided.

Default Bayesian testing for the scale parameters in two parameter exponential distributions

  • Kang, Sang Gil;Kim, Dal Ho;Lee, Woo Dong
    • Journal of the Korean Data and Information Science Society
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    • v.24 no.4
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    • pp.949-957
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    • 2013
  • In this paper, we consider the problem of testing the equality of the scale parameters in two parameter exponential distributions. We propose Bayesian testing procedures for the equality of the scale parameters under the noninformative priors. The noninformative prior is usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. Thus, we propose the default Bayesian testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. Simulation study and an example are provided.

Default Bayesian testing on the common mean of several normal distributions

  • Kang, Sang-Gil;Kim, Dal-Ho;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • v.23 no.3
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    • pp.605-616
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    • 2012
  • This article deals with the problem of testing on the common mean of several normal populations. We propose Bayesian hypothesis testing procedures for the common normal mean under the noninformative prior. The noninformative prior is usually improper and yields a calibration problem that makes the Bayes factor to be defined u to a multiplicative constant. So we propose the default Bayesian hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. Simulation study and an example are provided.

Default Bayesian testing for the equality of shape parameters in the inverse Weibull distributions

  • Kang, Sang Gil
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.6
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    • pp.1569-1579
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    • 2014
  • This article deals with the problem of testing for the equality of the shape parameters in two inverse Weibull distributions. We propose Bayesian hypothesis testing procedures for the equality of the shape parameters under the noninformative prior. The noninformative prior is usually improper which yields a calibration problem that makes the Bayes factor to be defined up to a multiplicative constant. So we propose the default Bayesian hypothesis testing procedures based on the fractional Bayes factor and the intrinsic Bayes factors under the reference priors. Simulation study and an example are provided.