Deng Dianliang, Sun Yiguang, Tian Guo-Liang
Department of Mathematics and Statistics, University of Regina, Regina, Canada.
Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen City, Guangdong, People's Republic of China.
J Appl Stat. 2021 Apr 24;49(11):2740-2766. doi: 10.1080/02664763.2021.1918649. eCollection 2022.
In this paper, a new multivariate zero-inflated binomial (MZIB) distribution is proposed to analyse the correlated proportional data with excessive zeros. The distributional properties of purposed model are studied. The Fisher scoring algorithm and EM algorithm are given for the computation of estimates of parameters in the proposed MZIB model with/without covariates. The score tests and the likelihood ratio tests are derived for assessing both the zero-inflation and the equality of multiple binomial probabilities in correlated proportional data. A limited simulation study is performed to evaluate the performance of derived EM algorithms for the estimation of parameters in the model with/without covariates and to compare the nominal levels and powers of both score tests and likelihood ratio tests. The whitefly data is used to illustrate the proposed methodologies.
本文提出了一种新的多元零膨胀二项分布（MZIB），用于分析具有过多零值的相关比例数据。研究了所提出模型的分布特性。给出了Fisher评分算法和EM算法，用于计算所提出的带/不带协变量的MZIB模型中参数的估计值。推导了得分检验和似然比检验，用于评估相关比例数据中的零膨胀和多个二项概率的相等性。进行了有限的模拟研究，以评估所推导的EM算法在带/不带协变量模型中参数估计的性能，并比较得分检验和似然比检验的名义水平和功效。使用粉虱数据来说明所提出的方法。
