• Journal of Korean Society for Atmospheric Environment
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• v.27 no.1
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• pp.41-49
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• 2011

The power plants are one of the GHG major source among the sectors of fossil fuel combustion, therefore information of its emission factors is very essential to the establishing control strategies for the greenhouse gas emissions. The $CH_4$ and $N_2O$ concentration from power plants were measured using GC-FID and GC-ECD. The results showed that $CH_4$ emission factor was 0.33 kg/TJ and $N_2O$ emission factor was 0.88 kg/TJ. The $CH_4$ and $N_2O$ emission factors developed in this study were compared with those for IPCC default value and other countries emission factors. The results showed that $CH_4$ emission factor was lower than IPCC default value and Finnish emission factor, but higher than Japanese emission factor. $N_2O$ emission factor was higher Japanese emission factor and IPCC default emission factor however lower than Finnish emission factor. More research is needed on our own emission factors of various energy-consuming facilities in order to stand on a higher position in international negotiations regarding the treaties on climate changes.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• 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.

• Journal of Climate Change Research
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• v.5 no.4
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• pp.349-357
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• 2014

Greenhouse gases (GHGs) from agricultural sector were categorized in a guideline book from Intergovernmental Panel on Climate Change (IPCC) as methane from rice paddy fields and nitrous oxide from agricultural soils. In general, GHG emissions were calculated by multiplying the activity data by emission factor. Tier 1 methodology uses IPCC default factors and Tier 2 uses country specific emission factors (CS). The CS and Scaling factors (SF) had been developed by NAAS (National Academy of Agricultural Science) projects from 2009 to 2012 to estimate how the advanced emissions. The purpose of this study was to compare GHG emissions calculated from IPCC default factors and NAAS CS and SF of agricultural sector in Korea. Methane emissions using CS and SF in rice paddy field was about 79% higher than those using IPCC default factors. In the agricultural soils, nitrous oxide emissions using CS from the 5 crops were about 40% lower than those using IPCC default. Except those 5 crops, approximately up to 52% lower emissions were calculated using CS compared to those using IPCC default factors. The total GHG emissions using CS and SF were about 33% higher than those using Tier 1 method by IPCC default factors.

• The Korean Journal of Applied Statistics
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• v.11 no.2
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• pp.435-449
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• 1998

In this article we have introduced a Bayes criterion for the variable selection in multiple discriminant analysis (MDA). The criterion is a default Bayes factor for the comparision of homo/heteroscadasticity of the multivariate normal means. The default Bayes factor is obtained from a development of the imaginary training sample method introduced by Spiegelhalter and Smith (1982). Based an the criterion, we also provided a test for additional discrimination in MDA. The advantage of the criterion is that it is not only applicable for the optimal subset selection method but for the stepwise method. More over, the criterion can be reduced to that for two-group discriminant analysis. Thus the criterion can be regarded as an unified alternative to variable selection criteria suggested by various sampling theory approaches. To illustrate the performance of the criterion, a numerical study has bean done via Monte Carlo experiment.