• Title/Summary/Keyword: statistical approach

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Optimal Software Release Policy for Random Cost Model

  • Kim, Hee-Soo;Shin, Mi-Young;Park, Dong-Ho
    • Communications for Statistical Applications and Methods
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    • v.12 no.3
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    • pp.673-682
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    • 2005
  • In this paper, we generalize the software reliability growth model by assuming that the testing cost and maintenance cost are random and adopt the Bayesian approach to determine the optimal software release time. Numerical examples are provided to illustrate the Bayesian method for certain parametric models.

Strong Large Deviations Theorems for the Ratio of the Independent Random Variables

  • Cho, Dae-Hyeon;Jeon, Jong-Woo
    • Journal of the Korean Statistical Society
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    • v.23 no.2
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    • pp.239-250
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    • 1994
  • In this paper, we prove a strong large deviations theorem for the ratio of independent randoem variables with error rate of $O(n^{-1})$. To obtain our results we use the inversion formula for the tail probability and apply the Chaganty and Sethuraman's (1985) approach.

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Monte Carlo Estimation of Multivariate Normal Probabilities

  • Oh, Man-Suk;Kim, Seung-Whan
    • Journal of the Korean Statistical Society
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    • v.28 no.4
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    • pp.443-455
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    • 1999
  • A simulation-based approach to estimating the probability of an arbitrary region under a multivariate normal distribution is developed. In specific, the probability is expressed as the ratio of the unrestricted and the restricted multivariate normal density functions, where the restriction is given by the region whose probability is of interest. The density function of the restricted distribution is then estimated by using a sample generated from the Gibbs sampling algorithm.

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Bayesian approach of weighting cell estimator

  • Lee Sangeun;Lee Juyoung;Lee Jinhee;Shin Minwoong
    • Proceedings of the Korean Statistical Society Conference
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    • 2000.11a
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    • pp.241-246
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    • 2000
  • A simple random sample is taken from a population and a particular survey item is subject to nonresponse that corresponds to random subsampling of the sampled values within adjustment cells. Our object is to estimate Bayesian probability interval of the population mean.

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AN EMPIRICAL BAYESIAN ESTIMATION OF MONTHLY LEVEL AND CHANGE IN TWO-WAY BALANCED ROTATION SAMPLING

  • Lee, Seung-Chun;Park, Yoo-Sung
    • Journal of the Korean Statistical Society
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    • v.32 no.2
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    • pp.175-191
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    • 2003
  • An empirical Bayesian approach is discussed for estimation of characteristics from the two-way balanced rotation sampling design which includes U.S. Current Population Survey and Canadian Labor Force Survey as special cases. An empirical Bayesian estimator is derived for monthly effect under presence of two types of biases and correlations It is shown that the marginal distribution of observation provides more general correlation structure than that frequentist has assumed. Consistent estimators are derived for hyper-parameters in Normal priors.

A General Mixed Linear Model with Left-Censored Data

  • Ha, Il-Do
    • Communications for Statistical Applications and Methods
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    • v.15 no.6
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    • pp.969-976
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    • 2008
  • Mixed linear models have been widely used in various correlated data including multivariate survival data. In this paper we extend hierarchical-likelihood(h-likelihood) approach for mixed linear models with right censored data to that for left censored data. We also allow a general random-effect structure and propose the estimation procedure. The proposed method is illustrated using a numerical data set and is also compared with marginal likelihood method.

Decision Analysis with Value Focused Thinking as a Methodology to Access Air Force Officer Retention Alternatives

  • Moon Sang-ho
    • Proceedings of the Korean Statistical Society Conference
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    • 2004.11a
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    • pp.105-110
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    • 2004
  • Decision Analysis(DA) using Value Focused Thinking(VFT) can be an excellent process to deal with hard decisions. The intent of this research is to provide better understanding of the United States Air Force(USAF) officer retention problem. This thesis effort involves building a VFT model to find out more effective alternatives in retaining pilots and non pilots. This model, in conjunction with the results of the post analysis, shows an example of the application of a VFT approach to the USAF officer retention problem.

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A Bayesian Approach to Paired Comparison of Several Products of Poisson Rates

  • Kim Dae-Hwang;Kim Hea-Jung
    • Proceedings of the Korean Statistical Society Conference
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    • 2004.11a
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    • pp.229-236
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    • 2004
  • This article presents a multiple comparison ranking procedure for several products of the Poisson rates. A preference probability matrix that warrants the optimal comparison ranking is introduced. Using a Bayesian Monte Carlo method, we develop simulation-based procedure to estimate the matrix and obtain the optimal ranking via a row-sum scores method. Necessary theory and two illustrative examples are provided.

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Noise-free Distributions Comparison of Bayesian Wavelet Threshold for Image Denoise

  • Choi, Ilsu;Rhee, Sung-Suk;Ahn, Yunkee
    • Communications for Statistical Applications and Methods
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    • v.8 no.2
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    • pp.573-579
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    • 2001
  • Wavelet thresholding is a method for he reduction of noise in image. Wavelet coefficients of image are correlated in local characterization. Thee correlations also appear in he original pixel representation of the image, and they do not follow from the characterizations of the wavelet transform. In this paper, we compare noise-free distributions of Bayes approach to improve the classical threshold algorithm.

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Bayes Prediction for Small Area Estimation

  • Lee, Sang-Eun
    • Communications for Statistical Applications and Methods
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    • v.8 no.2
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    • pp.407-416
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    • 2001
  • Sample surveys are usually designed and analyzed to produce estimates for a large area or populations. Therefore, for the small area estimations, sample sizes are often not large enough to give adequate precision. Several small area estimation methods were proposed in recent years concerning with sample sizes. Here, we will compare simple Bayesian approach with Bayesian prediction for small area estimation based on linear regression model. The performance of the proposed method was evaluated through unemployment population data form Economic Active Population(EAP) Survey.

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