• 제목/요약/키워드: binomial statistics

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Tests for homogeneity of proportions in clustered binomial data

  • Jeong, Kwang Mo
    • Communications for Statistical Applications and Methods
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    • 제23권5호
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    • pp.433-444
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    • 2016
  • When we observe binary responses in a cluster (such as rat lab-subjects), they are usually correlated to each other. In clustered binomial counts, the independence assumption is violated and we encounter an extra-variation. In the presence of extra-variation, the ordinary statistical analyses of binomial data are inappropriate to apply. In testing the homogeneity of proportions between several treatment groups, the classical Pearson chi-squared test has a severe flaw in the control of Type I error rates. We focus on modifying the chi-squared statistic by incorporating variance inflation factors. We suggest a method to adjust data in terms of dispersion estimate based on a quasi-likelihood model. We explain the testing procedure via an illustrative example as well as compare the performance of a modified chi-squared test with competitive statistics through a Monte Carlo study.

ON SOME MODELS LEADING TO QUASI-NEGATIVE-BINOMIAL DISTRIBUTION

  • Bilal, Sheikh;Hassan, Anwar
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제11권2호
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    • pp.15-29
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    • 2007
  • In this paper, we explore some interesting models of the quasi-negative-binomial distribution based on difference differential equations applicable to theory of microorganisms and the situations like that. Some characterizations based on conditional distributions and damage process have been obtained. Further, the distribution of number of accidents as the quasi-negative-binomial distribution in the light of Irwin's theory of ";proneness-liability"; model has been derived. Finally, the proposed model (QNBD) has been applied to study the Shunting accidents, home injuries, and strikes in industries.

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Effects of Overdispersion on Testing for Serial Dependence in the Time Series of Counts Data

  • Kim, Hee-Young;Park, You-Sung
    • Communications for Statistical Applications and Methods
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    • 제17권6호
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    • pp.829-843
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    • 2010
  • To test for the serial dependence in time series of counts data, Jung and Tremayne (2003) evaluated the size and power of several tests under the class of INARMA models based on binomial thinning operations for Poisson marginal distributions. The overdispersion phenomenon(i.e., a variance greater than the expectation) is common in the real world. Overdispersed count data can be modeled by using alternative thinning operations such as random coefficient thinning, iterated thinning, and quasi-binomial thinning. Such thinning operations can lead to time series models of counts with negative binomial or generalized Poisson marginal distributions. This paper examines whether the test statistics used by Jung and Tremayne (2003) on serial dependence in time series of counts data are affected by overdispersion.

이항-퇴화 혼합분포의 최우추정법 (Maximum likelihood estimation for a mixture distribution)

  • 황선영;손승혜;오창혁
    • Journal of the Korean Data and Information Science Society
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    • 제26권2호
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    • pp.313-322
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    • 2015
  • 본 연구에서는 하나의 균일분포 또는 퇴화분포와 두 개의 이항분포의 혼합분포 모형에 대하여 최우추정법을 소개하며, 제시된 모형에 대하여 시뮬레이션을 통해 최우추정량의 성질을 밝히며, 실험을 통해 얻은 강의 평가 자료에 대하여 퇴화분포를 가지는 혼합분포에 대하여 적용하여 보았다. 특히 퇴화분포는 한국의 문화 특성상 가운데 값을 선호하는 현상을 모형화하는데 유용하게 사용될 수 있음을 보였다.

이항 비율의 가중 POLYA POSTERIOR 구간추정 (Interval Estimation for a Binomial Proportion Based on Weighted Polya Posterior)

  • 이승천
    • 응용통계연구
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    • 제18권3호
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    • pp.607-615
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    • 2005
  • 최근 여러 학자들에 의해 이항 비율의 구간 추정에 많이 사용되고 있는 Wald 신뢰구 간의 문제점이 재조명되고 있고, 이에 대한 대안으로 이항 비율의 새로운 신뢰구간들이 발표되고 있다. 본 논문에서는 가중 Polya posterior를 이용한 베이지안 구간추정을 구하였다. 이 구간추정은 이항분포의 공액분포인 베타 사전분포에서 구한 전통적인 베이지안 구간추정과 같으나 추정의 편의를 위하여 정규근사에 의한 신뢰구간을 구할 때, 표본크기가 크면 실제적으로 Argresti와 Coull (1998)의 신뢰구간과도 일치하였다. 또 새로운 신뢰구간은 표본크기가 작은 경우와 비율이 극히 작은 경우에도 매우 유용한 신뢰구간이 된다는 것을 살펴보았다.

Coherent Forecasting in Binomial AR(p) Model

  • Kim, Hee-Young;Park, You-Sung
    • Communications for Statistical Applications and Methods
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    • 제17권1호
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    • pp.27-37
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    • 2010
  • This article concerns the forecasting in binomial AR(p) models which is proposed by Wei$\ss$ (2009b) for time series of binomial counts. Our method extends to binomial AR(p) models a recent result by Jung and Tremayne (2006) for integer-valued autoregressive model of second order, INAR(2), with simple Poisson innovations. Forecasts are produced by conditional median which gives 'coherent' forecasts, and we estimate the forecast distributions of future values of binomial AR(p) models by means of a Monte Carlo method allowing for parameter uncertainty. Model parameters are estimated by the method of moments and estimated standard errors are calculated by means of block of block bootstrap. The method is fitted to log data set used in Wei$\ss$ (2009b).

Sensory Difference Testing: The Problem of Overdispersion and the Use of Beta Binomial Statistical Analysis

  • Lee, Hye-Seong;O'Mahony, Michael
    • Food Science and Biotechnology
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    • 제15권4호
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    • pp.494-498
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    • 2006
  • An increase in variance (overdispersion) can occur when a binomial statistical analysis is applied to sensory difference test data in which replicate sensory evaluations (tastings) and multiple evaluators (judges) are combined to increase the sample size. Such a practice can cause extensive Type I errors, leading to serious misinterpretations of the data, especially when traditional simple binomial analysis is applied. Alternatively, the use of beta binomial analysis will circumvent the problem of overdispersion. This brief review discusses the uses and computation methodology of beta binomial analysis and in practice evidence for the occurrence of overdispersion.

Parametric Tests and Estimation of Mean Change in Discrete Distributions

  • Kim, Jae-Hee;Cheon, Soo-Young
    • Communications for Statistical Applications and Methods
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    • 제16권3호
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    • pp.511-518
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    • 2009
  • We consider the problem of testing for change and estimating the unknown change-point in a sequence of time-ordered observations from the binomial and Poisson distributions. Including the likelihood ratio test, Gombay and Horvath (1990) tests are studied and the proposed change-point estimator is derived from their test statistic. A power study of tests and a comparison study of change-point estimators are done via simulation.

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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