[英]Plotting smooth functions from a gam (using type = 'terms')
This is more of a follow up from a similar question asked recently, so hopefully this is a better/less vague question.这更像是对最近提出的类似问题的跟进,所以希望这是一个更好/不那么模糊的问题。
I have created a GAM and with to plot both smooth functions (on the same plot or two separate), what i'm failing with is how to plot the 2 columns i get in my predictions.我创建了一个 GAM 并绘制了两个平滑函数(在同一个图上或两个单独的图上),我失败的是如何绘制我在预测中得到的 2 列。 I need to keep month in my model for creating predictions due to the seasonal trend later down the line.由于稍后的季节性趋势,我需要在我的模型中保留一个月以创建预测。
mod = gam(co2 ~ s(timeStep, k = 200, bs = "cs") + s(month, k = 12, bs = "cc"),
data = carbonD,
family = gaussian(link = "identity"))
#predictions
preds = predict(carbonD_model3, newdata, type = 'terms', se.fit = TRUE)
preds$fit
s(timeStep) s(month)
1 -21.023636218 -0.44138402
2 -20.710943557 -0.36466359
3 -20.512344518 0.04800245
4 -20.532656726 1.15111508
5 -20.763446687 1.92491535
6 -21.120504411 1.80493059
#attempt at plotting but gives aesthetics errors
ggplot(newdata, aes(timeStep, co2)) +
geom_line(aes(timeStep, preds), col = 'red')
Also aware that this can be done someway like this (below), but would like to get my predictions working using this method is possible.也知道这可以像这样(如下)以某种方式完成,但想让我的预测使用这种方法是可能的。
plot(mod)
This works for me:这对我有用:
data(mtcars)
library(mgcv)
#> Loading required package: nlme
#> This is mgcv 1.8-40. For overview type 'help("mgcv-package")'.
library(ggplot2)
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following object is masked from 'package:nlme':
#>
#> collapse
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
m1 <- gam(mpg ~ s(hp) + s(wt), data=mtcars)
preds <- predict(m1, type="terms")
mf <- model.frame(m1)
mf <- bind_cols(mf, preds)
ggplot(mf, aes(x=hp, y=`s(hp)`)) +
geom_line()
ggplot(mf, aes(x=wt, y=`s(wt)`)) +
geom_line()
Created on 2022-06-27 by the reprex package (v2.0.1)由reprex 包(v2.0.1)于 2022-06-27 创建
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