• Title/Summary/Keyword: Statistics method

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BLOCK ITERATIVE METHODS FOR FUZZY LINEAR SYSTEMS

  • Wang, Ke;Zheng, Bing
    • Journal of applied mathematics & informatics
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    • v.25 no.1_2
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    • pp.119-136
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    • 2007
  • Block Jacobi and Gauss-Seidel iterative methods are studied for solving $n{\times}n$ fuzzy linear systems. A new splitting method is considered as well. These methods are accompanied with some convergence theorems. Numerical examples are presented to illustrate the theory.

On the Bias of Bootstrap Model Selection Criteria

  • Kee-Won Lee;Songyong Sim
    • Journal of the Korean Statistical Society
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    • v.25 no.2
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    • pp.195-203
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    • 1996
  • A bootstrap method is used to correct the apparent downward bias of a naive plug-in bootstrap model selection criterion, which is shown to enjoy a high degree of accuracy. Comparison of bootstrap method with the asymptotic method is made through an illustrative example.

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On the Implementation of Maximum-likelihood Factor Analysis

  • Song, Moon-Sup;Park, Chi-Hoon
    • Journal of the Korean Statistical Society
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    • v.9 no.1
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    • pp.13-29
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    • 1980
  • The statistical theory of factor analysis is briefly reviewed with emphasis on the maximum-likelihood method. A modified version of Joreskog(1975) is used for the implementation of the maximum-likelihood method. For the minimization of the conditional minimum function, an adaptive Newton-Raphson method is applied.

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Mathematics teachers' knowledge and belief on the high school probability and statistics (수학교사의 확률과 통계에 대한 지식과 신념)

  • Kim, Won-Kyung;Moon, So-Young;Byun, Ji-Young
    • The Mathematical Education
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    • v.45 no.4 s.115
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    • pp.381-406
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    • 2006
  • This work aims to investigate mathematics teachers' knowledge and belief on the high school probability and statistics. For this aim, two research questions are estabilished as follows. (1) How is mathematics teachers' knowledge on the main contents of the high school probability and statistics in the 7th mathematics curriculum? (2) What is mathematics teachers' belief on the high school probability and statistics? Survey and interviews were carried out to answer the above research questions. Subjects of the survey were 2 7mathematics teachers who were answered to questionnaire. Among them, 3 volunteers were chosen by provinces for in-depth interview. Research findings in mathematics teacher's knowledge are as follows. Firstly, mathematics teachers do not have much of mathematical knowledge on the newly added and changed contents of the high school probability and statistics in the 7th mathematics curriculum. Secondly, mathematics teachers do not change their teaching-learning method for probability and statistics. Thirdly, many teachers think that the use of technology and reconstruction of the textbooks are required in teaching and learning of the high school probability and statistics. But, they stick on their own way. Research findings in mathematics teachers' belief are as follows. Firstly, many mathematics teachers view the nature of statistics as a branch of the applied mathematics and put the value of high school probability and statistics on the practical usefulness, Secondly, many mathematics teachers think that understanding concepts and improving problem solving ability are the best method of the teaching and learning. Thirdly, many mathematics teachers think that high school probability and statistics textbooks should cause motivations and interests in order not to give up studying probability and statistics. It is expected that the above findings can be used to change teachers' teaching and learning methods and to improve teachers training program.

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Unsupervised Speaker Adaptation Based on Sufficient HMM Statistics (SUFFICIENT HMM 통계치에 기반한 UNSUPERVISED 화자 적응)

  • Ko Bong-Ok;Kim Chong-Kyo
    • Proceedings of the KSPS conference
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    • 2003.05a
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    • pp.127-130
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    • 2003
  • This paper describes an efficient method for unsupervised speaker adaptation. This method is based on selecting a subset of speakers who are acoustically close to a test speaker, and calculating adapted model parameters according to the previously stored sufficient HMM statistics of the selected speakers' data. In this method, only a few unsupervised test speaker's data are required for the adaptation. Also, by using the sufficient HMM statistics of the selected speakers' data, a quick adaptation can be done. Compared with a pre-clustering method, the proposed method can obtain a more optimal speaker cluster because the clustering result is determined according to test speaker's data on-line. Experiment results show that the proposed method attains better improvement than MLLR from the speaker independent model. Moreover the proposed method utilizes only one unsupervised sentence utterance, while MLLR usually utilizes more than ten supervised sentence utterances.

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Generating Multidimensional Random Tables (다차원 임의 분할표 생성)

  • Choi, Hyun-Jip
    • The Korean Journal of Applied Statistics
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    • v.19 no.3
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    • pp.545-554
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    • 2006
  • We suggest a method for generating multidimensional random tables based on the log-linear models. A linear combination approach by Lee(1997) is applied to get the joint distribution with the well known Pearson chi-squared statistics. We can generate completely associated joint distributions which have the fixed association among three variables by using the suggested method. Therefore the method can be extended to more higher dimension than the three dimensional tables.

A Comparative Study of Determining the Number of Clusters with a Method Proposed (군집수의 예측에 관한 방법의 제안 및 비교)

  • Chae, Seong-San;Lim, Nam-Kyoo
    • The Korean Journal of Applied Statistics
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    • v.18 no.2
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    • pp.329-341
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    • 2005
  • A method of determining the number of clusters is proposed based on some asymptotic results on the Rand's(1971} $C_k$, k = 2, 3, . . ., N - 1, statistic. Simulation is conducted to compare the proposed method with Chae and Warde(1991), and Huh and Lee(2004).

A Study for Obtaining Weights in Pairwise Comparison Matrix in AHP

  • Jeong, Hyeong-Chul;Lee, Jong-Chan;Jhun, Myoung-Shic
    • The Korean Journal of Applied Statistics
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    • v.25 no.3
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    • pp.531-541
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    • 2012
  • In this study, we consider various methods to estimate the weights of a pairwise comparison matrix in the Analytic Hierarchy Process widely applied in various decision-making fields. This paper uses a data dependent simulation to evaluate the statistical accuracy, minimum violation and minimum norm of the obtaining weight methods from a reciprocal symmetric matrix. No method dominates others in all criteria. Least squares methods perform best in point of mean squared errors; however, the eigenvectors method has an advantage in the minimum norm.

Accelerated Lifetime Data Analysis Using Quantile Regression (분위수 회귀를 이용한 가속수명시험 자료 분석)

  • Roh, Chee-Youn;Kim, Hee-Jeong;Na, Myung-Hwan
    • The Korean Journal of Applied Statistics
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    • v.21 no.4
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    • pp.631-638
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    • 2008
  • Accelerated Lifetime Test is a method of estimation of lifetime quality characteristics under operation condition with the accelerated lifetime data obtained under accelerated stress. In this paper we propose estimation method with accelerated lifetime data using quantile regression. We apply the method to real data with Arrhenius and Inverse power model.

A comparative study of the Gini coefficient estimators based on the regression approach

  • Mirzaei, Shahryar;Borzadaran, Gholam Reza Mohtashami;Amini, Mohammad;Jabbari, Hadi
    • Communications for Statistical Applications and Methods
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    • v.24 no.4
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    • pp.339-351
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    • 2017
  • Resampling approaches were the first techniques employed to compute a variance for the Gini coefficient; however, many authors have shown that an analysis of the Gini coefficient and its corresponding variance can be obtained from a regression model. Despite the simplicity of the regression approach method to compute a standard error for the Gini coefficient, the use of the proposed regression model has been challenging in economics. Therefore in this paper, we focus on a comparative study among the regression approach and resampling techniques. The regression method is shown to overestimate the standard error of the Gini index. The simulations show that the Gini estimator based on the modified regression model is also consistent and asymptotically normal with less divergence from normal distribution than other resampling techniques.