• Title/Summary/Keyword: Statistics Matching

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Noninformative Priors for the Ratio of the Lognormal Means with Equal Variances

  • Lee, Seung-A;Kim, Dal-Ho
    • Communications for Statistical Applications and Methods
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    • v.14 no.3
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    • pp.633-640
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    • 2007
  • We develop noninformative priors for the ratio of the lognormal means in equal variances case. The Jeffreys' prior and reference priors are derived. We find a first order matching prior and a second order matching prior. It turns out that Jeffreys' prior and all of the reference priors are first order matching priors and in particular, one-at-a-time reference prior is a second order matching prior. One-at-a-time reference prior meets very well the target coverage probabilities. We consider the bioequivalence problem. We calculate the posterior probabilities of the hypotheses and Bayes factors under Jeffreys' prior, reference prior and matching prior using a real-life example.

Environmental Survey Data Analysis by Data Fusion Technique

  • Cho, Kwang-Hyun;Park, Hee-Chang
    • 한국데이터정보과학회:학술대회논문집
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    • 2006.11a
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    • pp.21-27
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    • 2006
  • Data fusion is generally defined as the use of techniques that combine data from multiple sources and gather that information in order to achieve inferences. Data fusion is also called data combination or data matching. Data fusion is divided in five branch types which are exact matching, judgemental matching, probability matching, statistical matching, and data linking. Currently, Gyeongnam province is executing the social survey every year with the provincials. But, they have the limit of the analysis as execute the different survey to 3 year cycles. In this paper, we study to data fusion of environmental survey data using sas macro. We can use data fusion outputs in environmental preservation and environmental improvement.

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BAYESIAN TEST FOR THE EQUALITY OF THE MEANS AND VARIANCES OF THE TWO NORMAL POPULATIONS WITH VARIANCES RELATED TO THE MEANS USING NONINFORMATIVE PRIORS

  • Kim, Dal-Ho;Kang, Sang-Gil;Lee, Woo-Dong
    • Journal of the Korean Statistical Society
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    • v.32 no.3
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    • pp.271-288
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    • 2003
  • In this paper, when the variance of the normal distribution is related to the mean, we develop noninformative priors such as matching priors and reference priors. We prove that the second order matching prior matches alternative coverage probabilities up to the same order and also it is a HPD matching prior. It turns out that one-at-a-time reference prior satisfies a second order matching criterion. Then using these noninformative priors, we develop a Bayesian test procedure for the equality of the means and variances of two independent normal distributions using fractional Bayes factor. Some simulation study is performed, and a real data example is also provided.

Bayesian Analysis for Burr-Type X Strength-Stress Model

  • Kang, Sang-Gil;Ko, Jeong-Hwan;Lee, Woo-Dong
    • Proceedings of the Korea Society for Industrial Systems Conference
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    • 1999.05a
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    • pp.191-197
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    • 1999
  • In this paper, we develop noninformative priors that are used for estimating the reliability of stress-strength system under the Burr-type X distribution. A class of priors is found by matching the coverage probabilities of one-sided Bayesian credible interval with the corresponding frequentist coverage probabilities. It turns out that the reference prior is a first order matching prior. The propriety of posterior under matching prior is provided. The frequentist coverage probabilities are given for small samples.

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OBJECTIVE BAYESIAN APPROACH TO STEP STRESS ACCELERATED LIFE TESTS

  • Kim Dal-Ho;Lee Woo-Dong;Kang Sang-Gil
    • Journal of the Korean Statistical Society
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    • v.35 no.3
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    • pp.225-238
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    • 2006
  • This paper considers noninformative priors for the scale parameter of exponential distribution when the data are collected in step stress accelerated life tests. We find the Jeffreys' and reference priors for this model and show that the reference prior satisfies first order matching criterion. Also, we show that there exists no second order matching prior in this problem. Some simulation results are given and we perform Bayesian analysis for proposed priors using some data.

Developing Noninformative Priors for Parallel-Line Bioassay

  • Kim, YeongHwa;Heo, JungEun
    • Communications for Statistical Applications and Methods
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    • v.9 no.2
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    • pp.401-410
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    • 2002
  • This paper revisits parallel-line bioassay problem, from a Bayesian point of view using noninformative priors such as Jeffreys' prior, reference priors, and probability matching priors. After finding the orthogonal transformation, the class of first order and second order probability matching priors are derived. Jeffreys' prior and reference priors are derived also. Numerical examples are given to show the effectiveness of noninformative priors.

Bayesian Analysis for the Difference of Exponential Means

  • Kang, Sang-Gil;Kim, Dal-Ho;Lee, Woo-Dong
    • 한국데이터정보과학회:학술대회논문집
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    • 2005.04a
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    • pp.135-144
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    • 2005
  • In this paper, we develop the noninformative priors for the exponential models when the parameter of interest is the difference of two means. We develop the first and second order matching priors. We reveal that the second order matching priors do not exist. It turns out that Jeffreys' prior does not satisfy a first order matching criterion. The Bayesian credible intervals based on the first order matching meet the frequentist target coverage probabilities much better than the frequentist intervals of Jeffreys' prior.

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Bayesian Analysis for the Difference of Exponential Means

  • Kang, Sang-Gil;Kim, Dal-Ho;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.4
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    • pp.1067-1078
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    • 2005
  • In this paper, we develop the noninformative priors for the exponential models when the parameter of interest is the difference of two means. We develop the first and second order matching priors. We reveal that the second order matching priors do not exist. It turns out that Jeffreys' prior does not satisfy the first order matching criterion. The Bayesian credible intervals based on the first order matching meet the frequentist target coverage probabilities much better than the frequentist intervals of Jeffreys' prior.

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Noninformative Priors for the Common Scale Parameter in the Inverse Gaussian Distributions

  • Kang, Sang-Gil
    • Journal of the Korean Data and Information Science Society
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    • v.15 no.4
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    • pp.981-992
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    • 2004
  • In this paper, we develop the noninformative priors for the common scale parameter in the inverse gaussian distributions. We developed the first and second order matching priors. Next we revealed that the second order matching prior satisfies a HPD matching criterion. Also we showed that the second order matching prior matches alternative coverage probabilities up to the second order. It turns out that the one-at-a-time reference prior satisfies a second order matching criterion. Some simulation study is performed.

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Noninformative Priors for Stress-Strength System in the Burr-Type X Model

  • Kim, Dal-Ho;Kang, Sang-Gil;Cho, Jang-Sik
    • Journal of the Korean Statistical Society
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    • v.29 no.1
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    • pp.17-27
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    • 2000
  • In this paper, we develop noninformative priors that are used for estimating the reliability of stress-strength system under the Burr-type X model. A class of priors is found by matching the coverage probabilities of one-sided Bayesian credible interval with the corresponding frequentist coverage probabilities. It turns out that the reference prior as well as the Jeffreys prior are the second order matching prior. The propriety of posterior under the noninformative priors is proved. The frequentist coverage probabilities are investigated for samll samples via simulation study.

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