简体   繁体   English

R 中的零膨胀准泊松模型(glmmadmb、pscl)

[英]Zero-Inflated Quasi-Poisson Models in R (glmmadmb, pscl)

Q: Can a valid, zero-inflated Quasi-Poisson model be fitted in R?问:可以在 R 中拟合有效的零膨胀准泊松模型吗?

I know zero-inflated Poisson and zero-inflated negative binomial both can be fitted with each pscl::zeroinfl() and glmmADMB::glmmadmb() .我知道零膨胀泊松和零膨胀负二项式都可以适合每个pscl::zeroinfl()glmmADMB::glmmadmb()

However, in the help-file examples for pscl::zeroinfl() , the Quasi-poisson is fitted without inflation but omitted from the inflation demonstration:然而,在pscl::zeroinfl()的帮助文件示例中,拟泊松在没有通货膨胀的情况下安装,但在通货膨胀演示中被省略:

## data
data("bioChemists", package = "pscl")

## without inflation
## ("art ~ ." is "art ~ fem + mar + kid5 + phd + ment")
fm_pois  <- glm(   art ~ ., data = bioChemists, family = poisson)
fm_qpois <- glm(   art ~ ., data = bioChemists, family = quasipoisson)
fm_nb    <- glm.nb(art ~ ., data = bioChemists)

## with simple inflation (no regressors for zero component)
fm_zip  <- zeroinfl(art ~ . | 1, data = bioChemists)
fm_zinb <- zeroinfl(art ~ . | 1, data = bioChemists, dist = "negbin")

and the only options for dist are dist = c("poisson", "negbin", "geometric") . dist 的唯一选项是dist = c("poisson", "negbin", "geometric")

In the help-file documentation for glmmADMB::glmmadmb() , the negative binomial is family="nbinom" while the Quasi-Poisson is family="nbinom1" and the argument definition for zeroInflation states:glmmADMB::glmmadmb()的帮助文件文档中,负二项式是family="nbinom" ,而 Quasi-Poisson 是family="nbinom1"并且zeroInflation的参数定义指出:

zeroInflation: whether a zero-inflated model should be fitted 
              (only "poisson" and "nbinom" families).

My understanding is that Quasi-Poisson models have the advantage of accounting for overdispersion (albeit in a linear fashion);我的理解是,准泊松模型具有解决过度分散的优势(尽管是线性方式); that is if P is Poisson and Q is Quasi-Poisson:也就是说,如果 P 是泊松且 Q 是拟泊松:

在此处输入图像描述

but perhaps because they lack a proper likelihood they cannot be as easily implemented and that's why they are apparently omitted from two of the more popular zero-inflated packages...但也许是因为它们缺乏适当的可能性,所以它们不能那么容易地实施,这就是为什么它们显然被两个更流行的零膨胀包省略了......

Q: Can a valid, zero-inflated Quasi-Poisson model be fitted in R?问:可以在 R 中拟合有效的零膨胀准泊松模型吗?

A: YES, a valid, zero-inflated Quasi-Poisson model be fitted in R.答:是的,在 R 中安装了一个有效的、零膨胀的准泊松模型。

Set aside pscl::zeroinfl() and focus on glmmADMB::glmmadmb() .搁置pscl::zeroinfl()并专注于glmmADMB::glmmadmb()

A few things for glmmADMB::glmmadmb() : glmmADMB::glmmadmb()的一些内容:

  • family="nbinom1" is still a negative binomial model with a valid likelihood -- the help-file just states that the parameterization corresponds to a quasipoisson. family="nbinom1"仍然是一个具有有效可能性的负二项式模型——帮助文件只是说明参数化对应于拟泊松。 If you dig through the guts of glmmADMB::glmmadmb() you'll see that "nbinom", "nbinom1", and "nbinom2" are all changed to family="nbinom" and that specifying "nbinom1" just creates a flag to submit tau=alpha instead of tau=(1+e1+lambda/alpha) in the .tpl file .如果深入了解glmmADMB::glmmadmb() ,您会发现“nbinom”、“nbinom1”和“nbinom2”都已更改为family="nbinom" ,并且指定“nbinom1”只是创建一个标志以在.tpl 文件中提交tau=alpha而不是tau=(1+e1+lambda/alpha)

  • Furthermore, the package maintainer uses family="nbinom1" and zeroInflation=TRUE as the preferred model in an analysis about owls displayed on page 17 of a PDF at the ADMB website :此外,软件包维护者使用family="nbinom1"zeroInflation=TRUE作为ADMB 网站 PDF 第 17 页上显示的猫头鹰分析的首选模型:

    gfit3 <- glmmadmb(NCalls(FoodTreatment+ArrivalTime)*SexParent+ offset(logBroodSize)+(1|Nest), data=Owls, zeroInflation=TRUE, family="nbinom1") gfit3 <- glmmadmb(NCalls(FoodTreatment+ArrivalTime)*SexParent+ 偏移量(logBroodSize)+(1|Nest), data=Owls, zeroInflation=TRUE, family="nbinom1")

  • While this discussion is not about a zeroInflation=TRUE and family="nbinom1" model, Ben explains the parameterization of nbinom1 vs. quasi-poisson in the zeroInflation=FALSE case.虽然此讨论不是关于zeroInflation=TRUEfamily="nbinom1"模型,但 Ben 解释了 nbinom1 与zeroInflation=FALSE情况下的准泊松的参数化。

声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.

 
粤ICP备18138465号  © 2020-2024 STACKOOM.COM