R语言 negative.binomial 位于MASS 包(package)。 说明 使用glm() 指定使用已知 theta 参数拟合负二项式广义线性模型所需的信息。 用法 negative.binomial(theta = stop("'theta' must be specified"), link = "log") 参数 theta 附加参数 theta 的已知值。 link 链接函数,作为指定 log、 sqrt 或identity ...
The NB-GE GLM was applied to two over-dispersed crash datasets and its performance was compared to Negative Binomial-Lindley (NB-L) and Negative Binomial (NB) models using various statistical measures. It was found that NB-GE performs almost as well as NB-L model and performs much better ...
The negative binomial regression, which is a standard statis- tical method for analyzing over-dispersed count observa- tions, has been recently applied to microbiome data [28]. On the other hand, several zero-inflated models have also been proposed to correct for excess zero counts in ...
8 Negative binomial regression 8.1 Varieties of negative binomial 8.2 Derivation of the negative binomial 8.2.1 Poisson—gamma mixture model 8.2.2 Derivation of the GLM negative binomial 8.3 Negative binomial distributions 8.4 Negative binomial algorithms ...
在这种情况下,较为合适的做法是采用负二项回归模型 (negative binomial regression model,NBR regression) 。 负二项 回归模型的密度函数为 ㈧ = ( )～( ), - o. ,⋯, ㈠ 张萃:制造业 区域 集聚与技术创新 :基 于负二项模型的实证分析 109 其中,E(v IX ) = ,Var(yi xi) = (1...
zhangyuqing / ComBat-seq Star 160 Code Issues Pull requests Batch effect adjustment based on negative binomial regression for RNA sequencing count data rna-seq negative-binomial-regression batch-effects Updated Sep 24, 2020 R const-ae / glmGamPoi Star 105 Code Issues Pull requests Fit ...
作者:Joseph Michael Hilbe,Wiki简介:https://en.wikipedia.org/wiki/Joseph_Hilbe 负二项回归属于广义线性回归(GLM)的分支,与Logistic回归、Poisson回归等都属于计数数据模型的范畴,主要用于以分类变量、定序变量为因变量的回归分析之中。 负二项回归家族庞大,逐渐应用于社会科学领域各个学科的统计分析建模之中,本书...
Based on the output of trajectory inference, we applied tradeSeq in order to detect genes that displayed a strong differentiation between lineages. First, we ran tradeSeq fitGAM function to fit a negative binomial generalized additive model (NB-GAM) to the normalized count gene expression matrix,...
which can be used to derive a correspondingp-value. Note that if any of the cell counts are zero, the standard Wald test statisticTWis intractable (including 1/0 in the denominator). Similar results occur when fitting a logistic regression viaglm() in R where the variance is highly inflate...
The additional variability on the column margin in the contingency table results in the TND cell counts followed a multinomial distribution rather than a binomial distri- bution with one-way variability as in the case–control data. Therefore, the likelihood linked with the logistic regression is ...