ggplot2：在每個構面上添加回歸線方程時，x軸存在問題

Question

基於此處在圖上添加回歸線方程和R2的示例，我正在努力在每個方面都包括模型的回歸線方程。 但是，我不知道為什么要更改x軸的限制。

library(ggplot2)
library(reshape2)

df <- data.frame(year = seq(1979,2010), M02 = runif(32,-4,6), 
M06 = runif(32, -2.4, 5.1), M07 = runif(32, -2, 7.1))
df <- melt(df, id = c("year"))


ggplot(data = df, mapping = aes(x = year, y = value)) +
geom_point() +
scale_x_continuous() + 
stat_smooth_func(geom = 'text', method = 'lm', hjust = 0, parse = T) +
geom_smooth(method = 'lm', se = T) +
facet_wrap(~ variable) # as you can see, the scale_x_axis goes back to 1800

如果我在x上加上限制，

scale_x_continuous(limits = c(1979,2010)) 

它不再顯示回歸系數。 我在這里做錯了什么？

stat_smooth_func可以在這里找到： https ://gist.github.com/kdauria/524eade46135f6348140

Answer 1

您可以從ggpmisc軟件包中使用stat_poly_eq函數。

library(reshape2)
library(ggplot2)
library(ggpmisc)
#> For news about 'ggpmisc', please, see https://www.r4photobiology.info/
#> For on-line documentation see https://docs.r4photobiology.info/ggpmisc/

df <- data.frame(year = seq(1979,2010), M02 = runif(32,-4,6), 
                 M06 = runif(32, -2.4, 5.1), M07 = runif(32, -2, 7.1))
df <- melt(df, id = c("year"))

formula1 <- y ~ x

ggplot(data = df, mapping = aes(x = year, y = value)) +
  geom_point() +
  scale_x_continuous() + 
  geom_smooth(method = 'lm', se = TRUE) +
  stat_poly_eq(aes(label = paste(..eq.label.., ..rr.label.., sep = "~~~~")), 
               label.x = "left", label.y = "top",
               formula = formula1, parse = TRUE, size = 3) +
  facet_wrap(~ variable) 

ggplot(data = df, mapping = aes(x = year, y = value)) +
  geom_point() +
  scale_x_continuous() + 
  geom_smooth(method = 'lm', se = TRUE) +
  stat_poly_eq(aes(label = paste(..eq.label.., sep = "~~~")), 
               label.x = "left", label.y = 0.15,
               eq.with.lhs = "italic(hat(y))~`=`~",
               eq.x.rhs = "~italic(x)",
               formula = formula1, parse = TRUE, size = 4) +
  stat_poly_eq(aes(label = paste(..rr.label.., sep = "~~~")), 
               label.x = "left", label.y = "bottom",
               formula = formula1, parse = TRUE, size = 4) +
  facet_wrap(~ variable) 

^{由reprex軟件包 （v0.2.1.9000）創建於2019-01-10}

Answer 2

可能有人會建議一個更好的解決方案，但是作為替代，您可以更改stat_smooth_func，然后可以像這樣進行最后一行

data.frame(x=1979, y=ypos, label=func_string)

代替

data.frame(x=xpos, y=ypos, label=func_string)

因此，情節將如下所示