• 제목/요약/키워드: Kappa statistics

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Kullback-Leibler Information in View of an Extended Version of κ-Records

  • Ahmadi, Mosayeba;Mohtashami Borzadaran, G.R.
    • Communications for Statistical Applications and Methods
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    • 제20권1호
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    • pp.1-13
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    • 2013
  • This paper introduces an extended version of ${\kappa}$-records. Kullback-Leibler (K-L) information between two generalized distributions arising from ${\kappa}$-records is derived; subsequently, it is shown that K-L information does not depend on the baseline distribution. The behavior of K-L information for order statistics and ${\kappa}$-records, is studied. The exact expressions for K-L information between distributions of order statistics and upper (lower) ${\kappa}$-records are obtained and some special cases are provided.

A Study on Comparison of Generalized Kappa Statistics in Agreement Analysis

  • Kim, Min-Seon;Song, Ki-Jun;Nam, Chung-Mo;Jung, In-Kyung
    • 응용통계연구
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    • 제25권5호
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    • pp.719-731
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    • 2012
  • Agreement analysis is conducted to assess reliability among rating results performed repeatedly on the same subjects by one or more raters. The kappa statistic is commonly used when rating scales are categorical. The simple and weighted kappa statistics are used to measure the degree of agreement between two raters, and the generalized kappa statistics to measure the degree of agreement among more than two raters. In this paper, we compare the performance of four different generalized kappa statistics proposed by Fleiss (1971), Conger (1980), Randolph (2005), and Gwet (2008a). We also examine how sensitive each of four generalized kappa statistics can be to the marginal probability distribution as to whether marginal balancedness and/or homogeneity hold or not. The performance of the four methods is compared in terms of the relative bias and coverage rate through simulation studies in various scenarios with different numbers of raters, subjects, and categories. A real data example is also presented to illustrate the four methods.

LH-Moments of Some Distributions Useful in Hydrology

  • Murshed, Md. Sharwar;Park, Byung-Jun;Jeong, Bo-Yoon;Park, Jeong-Soo
    • Communications for Statistical Applications and Methods
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    • 제16권4호
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    • pp.647-658
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    • 2009
  • It is already known from the previous study that flood seems to have heavier tail. Therefore, to make prediction of future extreme label, some agreement of tail behavior of extreme data is highly required. The LH-moments estimation method, the generalized form of L-moments is an useful method of characterizing the upper part of the distribution. LH-moments are based on linear combination of higher order statistics. In this study, we have formulated LH-moments of five distributions useful in hydrology such as, two types of three parameter kappa distributions, beta-${\kappa}$ distribution, beta-p distribution and a generalized Gumbel distribution. Using LH-moments reduces the undue influences that small sample may have on the estimation of large return period events.

다상태 κ-out-of-n 시스템의 효율에 관한 연구 (Study on the Efficiency of Multi-State κ-out-of-n System)

  • 김지현;남해별;차지환
    • 응용통계연구
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    • 제26권1호
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    • pp.119-130
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    • 2013
  • 시스템을 구성하고 있는 $n$개의 부품 중 적어도 ${\kappa}$개의 부품이 제대로 작동하면 정상적으로 작동하는 시스템을 ${\kappa}$-out-of-$n$ 시스템이라 한다. 기존의 ${\kappa}$-out-of-$n$ 시스템에 관한 대부분의 연구에서는 단지 시스템의 작동여부에만 관심을 갖고 시스템의 신뢰도를 산출하는 문제를 주로 다루었다. 하지만 시스템이 작동할 때 작동하는 부품의 개수에 따라 시스템의 효율이 달라질 수 있으므로, 본 논문에서는 다상태 ${\kappa}$-out-of-$n$ 시스템을 고려하고 시스템의 총 효율을 산출하는 연구를 수행한다. 또한 시스템이 수리 가능할 경우, 시스템의 총 효율을 최대화 시킬 수 있는 수리 시점을 찾아보기로 한다. 이러한 시스템의 효율은 기존의 평균수명을 일반화한 형태가 됨을 보일 수 있다. 따라서 본 연구에서 다루는 모형은 기존의 모형을 보다 일반적인 경우로 확장한 모형이라 할 수 있다.

κ-공간중위 군집방법을 활용한 층화방법 (Stratification Method Using κ-Spatial Medians Clustering)

  • 손순철;전명식
    • 응용통계연구
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    • 제22권4호
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    • pp.677-686
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    • 2009
  • 표본조사에서 널리 쓰이는 모집단의 층화는 추정의 효율을 높이는 방법 중의 하나지만, 이상점을 포함하는 변수가 있는 경우에 여러 가지 문제점을 유발시킬 수 있다. 특히, 이상점이 존재하는 다변량 자료의 경우, 층화를 위한 $\kappa$-평균 군집방법은 이상점에 매우 민감하여 추정의 효율을 떨어뜨릴 수 있다. 본 연구에서는 이상점이 존재하는 다변량 자료의 층화를 위해 $\kappa$-평균 군집방법보다 강건하며 이상점을 따로 식별하는 과정이 배제된 $\kappa$-공간중위수 군집방법을 제안한다. 기존 관련연구인 박진우와 윤석훈 (2008)과 동일한 자료에 대한 사례분석을 통해 층화과정들을 비교, 검토하였으며 이들의 효율성을 추정량의 분산을 통해 비교하였다.

A WEAK LAW FOR WEIGHTED SUMS OF ARRAY OF ROW NA RANDOM VARIABLES

  • Baek, Jong-Il;Liang, Han-Ying;Choi, Jeong-Yeol
    • 대한수학회보
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    • 제40권2호
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    • pp.341-349
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    • 2003
  • Let {$x_{nk}\;$\mid$1\;\leq\;k\;\leq\;n,\;n\;\geq\;1$} be an array of random varianbles and $\{a_n$\mid$n\;\geq\;1\}\;and\;\{b_n$\mid$n\;\geq\;1} be a sequence of constants with $a_n\;>\;0,\;b_n\;>\;0,\;n\;\geq\;1. In this paper, for array of row negatively associated(NA) random variables, we establish a general weak law of large numbers (WLLA) of the form (${\sum_{\kappa=1}}^n\;a_{\kappa}X_{n\kappa}\;-\;\nu_{n\kappa})\;/b_n$ converges in probability to zero, as $n\;\rightarrow\;\infty$, where {$\nu_{n\kappa}$\mid$1\;\leq\;\kappa\;\leq\;n,\;n\;\geq\;1$} is a suitable array of constants.

Bayesian Estimation of the Two-Parameter Kappa Distribution

  • Oh, Mi-Ra;Kim, Sun-Worl;Park, Jeong-Soo;Son, Young-Sook
    • Communications for Statistical Applications and Methods
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    • 제14권2호
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    • pp.355-363
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    • 2007
  • In this paper a Bayesian estimation of the two-parameter kappa distribution was discussed under the noninformative prior. The Bayesian estimators are obtained by the Gibbs sampling. The generation of the shape parameter and scale parameter in the Gibbs sampler is implemented using the adaptive rejection Metropolis sampling algorithm of Gilks et al. (1995). A Monte Carlo study showed that the Bayesian estimators proposed outperform other estimators in the sense of mean squared error.

Acceptable Values of Kappa for Comparison of Two Groups

  • Seigel Daniel G.;Podgor Marvin J.;Remaley Nancy A.
    • 대한예방의학회:학술대회논문집
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    • 대한예방의학회 1994년도 교수 연수회(역학)
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    • pp.129-136
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    • 1994
  • A model was developed for a simple clinical trial in which graders had defined probabilities of misclassifying pathologic material to disease present or absent. The authors compared Kappa between graders, and efficiency and bias in the clinical trial in the presence of misclassification. Though related to bias and efficiency, Kappa did not predict these two statistics well. These results pertain generally to evaluation of systems for encoding medical information, and the relevance of Kappa in determining whether such systems are ready for use in comparative studies. The authors conclude that, by itself, Kappa is not informative Enough to evaluate the appropriateness of a grading scheme for comparative studies. Additional, and perhaps difficult, questions must be addressed for such evaluation.

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Adaptive Nearest Neighbors를 활용한 판별분류방법 (Adaptive Nearest Neighbors for Classification)

  • 전명식;최인경
    • 응용통계연구
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    • 제22권3호
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    • pp.479-488
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    • 2009
  • 비모수적 판별분류방법으로 널리 사용되는 ${\kappa}$-Nearest Neighbors Classification(KNNC) 방법은 자료의 국소적 특징을 고려하지 않고 전체 자료에 대해 고정된 이웃의 개수 ${\kappa}$를 사용하여 개체를 분류하는 방법이다. 본 연구에서는 KNNC의 대안으로 자료의 국소적 특징을 고려하는 Adaptive Nearest Neighbors Classificaion(ANNC) 방법을 제안하였다. 제안된 방법의 특징을 규명하기 위하여 실제 자료에 대한 분석을 통하여 제안된 방법의 응용 가능성을 제시하였으며, 나아가 모의실험을 통하여 기존의 방법과의 효율성을 비교하였다.

STRONG VERSIONS OF κ-FRÉCHET AND κ-NET SPACES

  • CHO, MYUNG HYUN;KIM, JUNHUI;MOON, MI AE
    • 호남수학학술지
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    • 제37권4호
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    • pp.549-557
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    • 2015
  • We introduce strongly ${\kappa}$-$Fr{\acute{e}}chet$ and strongly ${\kappa}$-sequential spaces which are stronger than ${\kappa}$-$Fr{\acute{e}}chet$ and ${\kappa}$-net spaces respectively. For convenience, we use the terminology "${\kappa}$-sequential" instead of "${\kappa}$-net space", introduced by R.E. Hodel in [5]. And we study some properties and topological operations on such spaces. We also define strictly ${\kappa}$-$Fr{\acute{e}}chet$ and strictly ${\kappa}$-sequential spaces which are more stronger than strongly ${\kappa}$-$Fr{\acute{e}}chet$ and strongly ${\kappa}$-sequential spaces respectively.