疏通全球模型未能收敛 [英] Dredge with the global model failing to converge

问题描述

我正在尝试在疏浚 (MuMIn) 框架中运行具有多个变量组合的 gamm 模型，并将基于截止的 TRUE/FALSE 相关矩阵作为子集.

I am trying to run gamm models with multiple variable combinations in dredge (MuMIn) framework, with a cutoff based TRUE/FALSE correlation matrix as subset.

问题是，我的完整模型非常复杂，具有随机效应，>20 个预测变量包括 3 个固定效应，因此不会收敛.我的预测变量是高度相关的，正如前面提到的，我包含了一个 TRUE/FALSE 相关矩阵作为子集.由于相关性截止值较低，我预计组合很少，并且对完整模型并不真正感兴趣.

Problem is, my full model is quite complex with random effects, >20 predictor variables including 3 fixed effects, and therefore won't converge. My predictors are highly correlated, as mentioned I included a TRUE/FALSE correlation matrix as subset. Due a low correlation cutoff I expect very few combinations and not really interested in the full model.

但是，我构建的 gamm(或 uGamm)完整模型包含 20 多个预测变量(平滑项和固定效应、随机效应)并没有收敛.这基本上意味着挖泥机不会运行，因为完整模型不会收敛，即使我对完整模型本身不感兴趣，而是对单个模型和一些组合不感兴趣.

However, my construction of gamm (or uGamm) full model, which includes 20+ predictors (smoothed terms and fixed effects, random effects) does not converge. This essentially means that dredge won't run since the full model doesn't converge, even though I am not interested in the full model per se, rather in the single models and a few combinations.

看来我也不能使用 fm1 <- gamm(y ~ (.), data = Cement) 选项，因为这会产生以下错误:

It also appears that I cant use fm1 <- gamm(y ~ (.), data = Cement) option, as this gives the following error:

s(.) 中的错误:s(.) 尚不支持

Error in s(.) : s(.) not yet supported

有没有办法绕过不会收敛并且无论如何都有我的变量组合的完整模型?和/或有没有办法用 (.) 避免上述错误?

Is there a way to bypass the full model which will not converge and have my variable combinations regardless? and/Or is there a way to avoid the above error with (.)?

有什么建议吗?我的数据太大，无法包含在此处.

Any suggestions? my data is too large to include here.

推荐答案

您可以通过替换更简单模型中的公式来欺骗 dredge，然后将该模型用作全局模型".将完整的模型公式分配给 ;$ 游戏 $ 公式.例如:

You can trick dredge by replacing the formula in a simpler model, and then use that model as a "global model". Assign the full model formula to <gam.model> $ gam $ formula. For example:

# fit some simple model
fm <- uGamm(y ~ s(x1), ...) # add other arguments as in the proper full model
fm$gam$formula <- y ~ x0 + s(x1) + s(x2) + ... + s(xn)
dredge(fm) 

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