• 제목/요약/키워드: binomial distribution

검색결과 217건 처리시간 0.024초

한국어 음소분포에 대한 계량언어학적 연구 - "소"와 "고도를 기다리며"를 중심으로 - (A Quantitative Study for the Distribution of Korean Phonemes in the two parts: The Ox and Waiting for Godot)

  • 배희숙;구동욱;윤영선;오영환
    • 음성과학
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    • 제7권4호
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    • pp.27-40
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    • 2000
  • The goal of quantitative linguistics is to show the quantitative behavior of linguistic units. There are several studies which examine the frequency of Korean phonemes, which are important in comprehending the internal function of the linguistic units. However, the frequency information, from the pure phonological level without any consideration of rhythmic group, cannot adequately represent linguistic phenomena. Therefore, to provide the effective information, the phonological transcription must be carried out on the level of rhythmic group. In this paper, we made the transcription to analyze Korean phonology. We were not satisfied with merely investigating the frequencies of the phonemes, but also examined whether the distribution of Korean phonemes show the binomial distribution within linguistic constraints.

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Effects on Regression Estimates under Misspecified Generalized Linear Mixed Models for Counts Data

  • Jeong, Kwang Mo
    • 응용통계연구
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    • 제25권6호
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    • pp.1037-1047
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    • 2012
  • The generalized linear mixed model(GLMM) is widely used in fitting categorical responses of clustered data. In the numerical approximation of likelihood function the normality is assumed for the random effects distribution; subsequently, the commercial statistical packages also routinely fit GLMM under this normality assumption. We may also encounter departures from the distributional assumption on the response variable. It would be interesting to investigate the impact on the estimates of parameters under misspecification of distributions; however, there has been limited researche on these topics. We study the sensitivity or robustness of the maximum likelihood estimators(MLEs) of GLMM for counts data when the true underlying distribution is normal, gamma, exponential, and a mixture of two normal distributions. We also consider the effects on the MLEs when we fit Poisson-normal GLMM whereas the outcomes are generated from the negative binomial distribution with overdispersion. Through a small scale Monte Carlo study we check the empirical coverage probabilities of parameters and biases of MLEs of GLMM.

과대산포 가산자료의 새로운 표본선택모형 (A new sample selection model for overdispersed count data)

  • 조성은;조준;김형문
    • 응용통계연구
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    • 제31권6호
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    • pp.733-749
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    • 2018
  • 어떠한 연구에서 관심의 대상이 되는 관찰치가 부분적으로 관측 가능할 때 표본선택의 문제가 일어난다. 이러한 자료를 분석하기 위해 헤크만은 표본선택 모형을 개발하였고 이변량 정규분표의 가정 하에 최대우도방법을 사용하여 모수를 추정하였다. 최근 이항자료와 포아송 자료에 대한 표본선택모형이 제안되었다. 이를 분포조정에 기초하여 과대산포 자료에 대한 모형으로 확장하고자 한다. 표본선택이 없는 과대산포 자료는 흔히 음이항 분포로 분석되어진다. 따라서 음이항 분포를 이용하고 분포조정을 도입한 과대산포 자료에 대한 새로운 모형을 제시하고자 한다. 실제 자료를 이용하여 분석을 하였다. 모의실험 결과 프로파일 우도함수를 이용하여 모수에 대해 추정한 결과는 안정적이다.

음이항분포 정보를 가진 베이지안 소프트웨어 신뢰도 성장모형에 관한 연구 (Bayesian Analysis of Software Reliability Growth Model with Negative Binomial Information)

  • 김희철;박종구;이병수
    • 한국정보처리학회논문지
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    • 제7권3호
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    • pp.852-861
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    • 2000
  • Software reliability growth models are used in testing stages of software development to model the error content and time intervals betwewn software failures. In this paper, using priors for the number of fault with the negative binomial distribution nd the error rate with gamma distribution, Bayesian inference and model selection method for Jelinski-Moranda and Goel-Okumoto and Schick-Wolverton models in software reliability. For model selection, we explored the sum of the relative error, Braun statistic and median variation. In Bayesian computation process, we could avoid the multiple integration by the use of Gibbs sampling, which is a kind of Markov Chain Monte Carolo method to compute the posterior distribution. Using simulated data, Bayesian inference and model selection is studied.

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베이지안 음이항 분기과정을 이용한 한국 메르스 발생 연구 (A study on MERS-CoV outbreak in Korea using Bayesian negative binomial branching processes)

  • 박유하;최일수
    • Journal of the Korean Data and Information Science Society
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    • 제28권1호
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    • pp.153-161
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    • 2017
  • 전염병 확산에 대한 확률과정모형으로 활용되는 분기과정은 실제 데이터를 통해 모수를 추정할 수 있다는 장점이 있다. 음이항 분포를 분기과정의 생산 분포 모형으로 적용할 수 있는데 음이항 분포를 적용하기 위해서는 평균과 산포 모수를 추정하여야한다. 기존의 생물학 연구와 역학 연구 분야에서는 이를 최대우도법을 이용하여 추정하고 있다. 그러나 대부분의 역학 자료의 특성상 분기과정에서 이용되는 음이항 분포는 소표본이어서 최대우도 추정량의 정도를 충족시킬 수 없다. 본 논문에서는 소표본 자료에서 좋은 통계량의 성질을 만족한다고 알려져 있는 베이지안을 이용하여 모수를 추정하는 방법을 제안한다. 2015년 국내 메르스 사례에 베이지안 방법을 적용하여 모수를 추정하고 사후 분포를 적합하였다. 그 결과 어떠한 사전 분포를 가정하더라도 안정적으로 모수를 추정하는 것을 알 수 있었다. 추정된 산포 모수를 이용하여 분기과정에서의 전염병 소멸 확률을 유도하였다.

Computer Program Development for Probability Distribution

  • Choi, Hyun-Seok;Song, Gyu-Moon
    • Journal of the Korean Data and Information Science Society
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    • 제16권3호
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    • pp.581-589
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    • 2005
  • The purpose of this thesis is to develop and introduce Add-in program which we can systematically, visually and dynamically study discrete probability distribution of binomial distribution, poisson distribution and hypergeometric distribution, and continuous probability distribution of normal distribution, exponential distribution, and the definition and characteristics of t distribution, F distribution and ${\chi}^2$ distribution to be driven from normal distribution, and graphs, the computation process of probability by using VBA which is the device of Excel.

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On a Generalized Inverse Binomial Sampling Plan

  • Bai, Do-Sun;Kim, Seong-In;Lee, Jung-Kyun
    • Journal of the Korean Statistical Society
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    • 제6권1호
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    • pp.3-20
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    • 1977
  • In many applications one is concerned with repeated Bernoulli trials whose parameter (success probability) is usually unknown and has to be estimated from a sample. The probability distribution and statistical inference on the repeated independent Bernoulli trials have been studied extensively for the cases of fixed sample size sampling plan, and inverse binomial sampling plan in which observations are cotinued until a pressigned number of successes are obtained. See, for example, Haldane, Girschick et al., DeGroot and Johnson and Kotz.

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A Simulation Study for the Confidence Intervals of p by Using Average Coverage Probability

  • Kim, Daehak;Jeong, Hyeong-Chul
    • Communications for Statistical Applications and Methods
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    • 제7권3호
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    • pp.859-869
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    • 2000
  • In this paper, various methods for finding confidence intervals for p of binomial parameter are reviewed. Also we introduce tow bootstrap confidence intervals for p. We compare the performance of bootstrap methods with other methods in terms of average coverage probability by Monte Carlo simulation. Advantages of these bootstrap methods are discussed.

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Bayesian Multiple Comparison of Binomial Populations based on Fractional Bayes Factor

  • Kim, Dal-Ho;Kang, Sang-Gil;Lee, Woo-Dong
    • Journal of the Korean Data and Information Science Society
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    • 제17권1호
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    • pp.233-244
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    • 2006
  • In this paper, we develop the Bayesian multiple comparisons procedure for the binomial distribution. We suggest the Bayesian procedure based on fractional Bayes factor when noninformative priors are applied for the parameters. An example is illustrated for the proposed method. For this example, the suggested method is straightforward for specifying distributionally and to implement computationally, with output readily adapted for required comparison. Also, some simulation was performed.

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