我有一个看起来像这样的数据集：
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2018.84873374401, 2018.86789869952, 2018.88706365503, 2018.90622861054,
2018.92539356605, 2018.94455852156, 2018.96372347707, 2018.98288843258,
2019.00205338809, 2019.0212183436, 2019.04038329911, 2019.05954825462,
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2019.23203285421, 2019.25119780972, 2019.27036276523, 2019.28952772074,
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2019.84531143053, 2019.86447638604, 2019.88364134155, 2019.90280629706,
2019.92197125257, 2019.94113620808, 2019.96030116359, 2019.9794661191
))
我正在运行看起来像这样的游戏：
CSA1.offset.gam.week<-gam(landings~ s(Date, bs = "tp") + s(month, bs = "cc", k=12) + offset(log(effort)),
data = CSA1.effort.land.week2, family = nb, method="REML")
我希望使用predict.gam（）在ggplot中绘制数据，但是由于存在偏移而出现问题。
当我像这样使用predict.gam（）来向我的数据集添加拟合和SE时，它看起来像这样：
cbind(CSA1.effort.land.week2,
predict.gam(CSA1.offset.gam.week,
se.fit=TRUE,
type="response",
terms="s(Date)"))
当我绘制此拟合图时，它显示为锯齿状的线性模型。
<< img src =“ https://image.soinside.com/eyJ1cmwiOiAiaHR0cHM6Ly9pLnN0YWNrLmltZ3VyLmNvbS9rcGxvci5wbmcifQ==” alt =“这是我绘制数据时的样子”>
[当我删除偏移量时，我看到一个GAM与我期望的GAM看起来一样，但我需要将此偏移量包含在我的数据中。
这是没有偏移量的GAM：
CSA1.offset.gam.week
This is what that GAM looks like with the same predict.gam function as the previous example
如果我打算保留偏移量，我应该如何在此GAM上使用predict.gam函数？？
我有一个看起来像这样的数据集：structure（list（effort = c（2633，7871，10273，5202，8550，4698，7357，3670，8933，8301，4416，5355，443，8946，11168，14572 ，15552，13947，7969，7541，27478，...
锯齿状来自使用不同（观察到的）努力值的预测。数据来自不同的工作，因此，如果您想将模型输出与数据进行比较，则需要提供观察到的偏移量。