如何在R中对特定数据集使用predict并在ggplot2中绘制？

我有如下数据：

time level     strain
   <dbl> <dbl>      <chr>
 1   0.0 0.000 M12-611020
 2   1.0 0.088 M12-611020
 3   3.0 0.211 M12-611020
 4   4.0 0.278 M12-611020
 5   4.5 0.404 M12-611020
 6   5.0 0.606 M12-611020
 7   5.5 0.778 M12-611020
 8   6.0 0.902 M12-611020
 9   6.5 1.024 M12-611020
10   8.0 1.100 M12-611020
11   0.0 0.000 M12-611025
12   1.0 0.077 M12-611025
13   3.0 0.088 M12-611025
14   4.0 0.125 M12-611025
15   5.0 0.304 M12-611025
16   5.5 0.421 M12-611025
17   6.0 0.518 M12-611025
18   6.5 0.616 M12-611025
19   7.0 0.718 M12-611025

然后，我想使用拟合的黄土曲线进行预测，如下所示：

# define the model
model <- loess(time ~ strain,span = 0.8, data = data)

# Predict for given levle (x) the time (y)
predict(model, newdata = 0.3, se = FALSE)

#定义模型
你的意思是这样的吗

p <- ggplot(data = dat, aes(x = time, y = level, fill = strain)) + 
  geom_point(alpha=0.5 , size=3,shape = 21, colour = "black", stroke = 1) +
  stat_smooth(aes(group=strain, colour=strain) ,method = "loess", se = F, span = 0.8)


newdat <- split(dat, dat$strain)
mod <- lapply(newdat, function(x)loess(level ~ time,span = 0.8, data = x))  

predict(mod[["M12-611020"]], newdata = 2, se = FALSE)

p + 
  geom_segment(aes(x=2, xend=2, y=0, yend=0.097), linetype="dashed") + 
  geom_segment(aes(x=0, xend=2, y=0.097, yend=0.097), linetype="dashed")

p是的，这真的很有帮助。我只是想知道ggplot2中是否有我丢失的内置函数？对于预测和预测绘图而言，黄土是一种更平滑的材料，实际上并不用于预测目的。您应该查看非线性或广义线性模型，而不是报告预测。
p <- ggplot(data = dat, aes(x = time, y = level, fill = strain)) + 
  geom_point(alpha=0.5 , size=3,shape = 21, colour = "black", stroke = 1) +
  stat_smooth(aes(group=strain, colour=strain) ,method = "loess", se = F, span = 0.8)


newdat <- split(dat, dat$strain)
mod <- lapply(newdat, function(x)loess(level ~ time,span = 0.8, data = x))  

predict(mod[["M12-611020"]], newdata = 2, se = FALSE)

p + 
  geom_segment(aes(x=2, xend=2, y=0, yend=0.097), linetype="dashed") + 
  geom_segment(aes(x=0, xend=2, y=0.097, yend=0.097), linetype="dashed")