• Title/Summary/Keyword: Log data

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Likelihood Based Inference for the Shape Parameter of the Inverse Gaussian Distribution

  • Lee, Woo-Dong;Kang, Sang-Gil;Kim, Dong-Seok
    • Communications for Statistical Applications and Methods
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    • v.15 no.5
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    • pp.655-666
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    • 2008
  • Small sample likelihood based inference for the shape parameter of the inverse Gaussian distribution is the purpose of this paper. When shape parameter is of interest, the signed log-likelihood ratio statistic and the modified signed log-likelihood ratio statistic are derived. Hsieh (1990) gave a statistical inference for the shape parameter based on an exact method. Throughout simulation, we will compare the statistical properties of the proposed statistics to the statistic given by Hsieh (1990) in term of confidence interval and power of test. We also discuss a real data example.

Graphical Methods for Hierarchical Log-Linear Models

  • Hong, Chong-Sun;Lee, Ui-Ki
    • Communications for Statistical Applications and Methods
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    • v.13 no.3
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    • pp.755-764
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    • 2006
  • Most graphical methods for categorical data can describe the structure of data and represent a measure of association among categorical variables. Among them the polyhedron plot represents sequential relationships among hierarchical log-linear models for a multidimensional contingency table. This kind of plot could be explored to describe the differences among sequential models. In this paper we suggest graphical methods, containing all the information, that reflect the relationship among all log-linear models in a certain hierarchical structure. We use the ideas of a correlation diagram.

A Development Study of Tool for Web Log Analysis

  • Choi, Seungbae;Kang, Changwan;Kim, Kyukon;Son, Jongkwan
    • Communications for Statistical Applications and Methods
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    • v.11 no.1
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    • pp.93-106
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    • 2004
  • Recently, many data of various types is gained with development of computer in many fields. Especially, web log data generating in web site furnish beneficial information on an organization. The enterprise's destiny is swayed by according as how these information gaining from the web site utilize. In this paper, for the purpose of obtaining useful information, we present a tool is called WebBizi for web log analysis. This will be helpful to enterprise working the web site.

A Study of Log-Fourier Deconvolution

  • Ja Yong Koo;Hyun Suk Park
    • Communications for Statistical Applications and Methods
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    • v.4 no.3
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    • pp.833-845
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    • 1997
  • Fourier expansion is considered for the deconvolution problem of estimating a probability density function when the sample observations are contaminated with random noise. In the log-Fourier method of density estimation for data without noise, the logarithm of the unknown density function is approximated by a trigonometric function, the unknown parameters of which are estimated by maximum likelihood. The log-Fourier density estimation method, which has been considered theoretically by Koo and Chung (1997), is studied for the finite-sample case with noise. Numerical examples using simulated data are given to show the performance of the log-Fourier deconvolution.

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A Dual Log-polar Map Rotation and Scale-Invariant Image Transform

  • Lee, Gang-Hwa;Lee, Suk-Gyu
    • International Journal of Precision Engineering and Manufacturing
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    • v.9 no.4
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    • pp.45-50
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    • 2008
  • The Fourier-Mellin transform is the theoretical basis for the translation, rotation, and scale invariance of an image. However, its implementation requires a log-polar map of the original image, which requires logarithmic sampling of a radial variable in that image. This means that the mapping process is accompanied by considerable loss of data. To solve this problem, we propose a dual log-polar map that uses both a forward image map and a reverse image map simultaneously. Data loss due to the forward map sub-sampling can be offset by the reverse map. This is the first step in creating an invertible log-polar map. Experimental results have demonstrated the effectiveness of the proposed scheme.

Web Server Log Visualization

  • Kim, Jungkee
    • International journal of advanced smart convergence
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    • v.7 no.4
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    • pp.101-107
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    • 2018
  • Visitors to a Web site leave access logs documenting their activity in the site. These access logs provide a valuable source of information about the visitors' access patterns in the Web site. In addition to the pages that the user visited, it is generally possible to discover the geographical locations of the visitors. Web servers also records other information such as the entry into the site, the URL, the used operating system and the browser, etc. There are several Web mining techniques to extract useful information from such information and visualization of a Web log is one of those techniques. This paper presents a technique as well as a case a study of visualizing a Web log.

Noninformative priors for the log-logistic distribution

  • 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.1
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    • pp.227-235
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    • 2014
  • In this paper, we develop the noninformative priors for the scale parameter and the shape parameter in the log-logistic distribution. We developed the first and second order matching priors. It turns out that the second order matching prior matches the alternative coverage probabilities, and is a highest posterior density matching prior. Also we revealed that the derived reference prior is the second order matching prior for both parameters, but Jerffrey's prior is not a second order matching prior. We showed that the proposed reference prior matches the target coverage probabilities in a frequentist sense through simulation study, and an example based on real data is given.

Quantitative Analysis of Coal Logging Data (석탄층 검층자료의 정량적 해석법 연구)

  • Kwon, Byung Doo;Son, Se Jo;Son, Jeong Woo
    • Economic and Environmental Geology
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    • v.21 no.1
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    • pp.85-96
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    • 1988
  • Geophysical well logging at various coal fields were carried out to study the characteristic response of domestic coal seams. Also a computer program is developed for quantitative analysis of coal logging data. Most coal seams penetrated by the drill holes, where the well logging were carried out, showed poor thickness and quality, and were severely altered. Therefore, majority of log data are inadequate for detailed quantitative analysis. The logs show, however, typical characteristics with related to coal seams, but interpretation should be made with caution because certain log response of demestic coals, mostly anthracite, are quite different to those of foreign coals, mostly bituminous. The developed comuter program has been proved as an effective one for identification of coal seams and lithology anslysis, and is expected to be succesfully used for coal quality analysis in cases of more diversified log data of good quality being obtained.

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Mutual Information and Redundancy for Categorical Data

  • Hong, Chong-Sun;Kim, Beom-Jun
    • Communications for Statistical Applications and Methods
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    • v.13 no.2
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    • pp.297-307
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    • 2006
  • Most methods for describing the relationship among random variables require specific probability distributions and some assumptions of random variables. The mutual information based on the entropy to measure the dependency among random variables does not need any specific assumptions. And the redundancy which is a analogous version of the mutual information was also proposed. In this paper, the redundancy and mutual information are explored to multi-dimensional categorical data. It is found that the redundancy for categorical data could be expressed as the function of the generalized likelihood ratio statistic under several kinds of independent log-linear models, so that the redundancy could also be used to analyze contingency tables. Whereas the generalized likelihood ratio statistic to test the goodness-of-fit of the log-linear models is sensitive to the sample size, the redundancy for categorical data does not depend on sample size but its cell probabilities itself.

MLE for Incomplete Contingency Tables with Lagrangian Multiplier

  • Kang, Shin-Soo
    • Journal of the Korean Data and Information Science Society
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    • v.17 no.3
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    • pp.919-925
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    • 2006
  • Maximum likelihood estimate(MLE) is obtained from the partial log-likelihood function for the cell probabilities of two way incomplete contingency tables proposed by Chen and Fienberg(1974). The partial log-likelihood function is modified by adding lagrangian multiplier that constraints can be incorporated with. Variances of MLE estimators of population proportions are derived from the matrix of second derivatives of the loglikelihood with respect to cell probabilities. Simulation results, when data are missing at random, reveal that Complete-case(CC) analysis produces biased estimates of joint probabilities under MAR and less efficient than either MLE or MI. MLE and MI provides consistent results under either the MAR situation. MLE provides more efficient estimates of population proportions than either multiple imputation(MI) based on data augmentation or complete case analysis. The standard errors of MLE from the proposed method using lagrangian multiplier are valid and have less variation than the standard errors from MI and CC.

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