如何在每个方面添加两个回归线方程和r2？

我想在每个方面添加两个回归线方程和r2。我采用了这个方法来解决这个问题，但我发现每个方程都是一样的。可能的原因是向函数发送错误的数据子集。任何建议都将不胜感激

我的代码：

p <- ggplot(data=df,aes(x=x))+
  geom_point(aes(y = y1),size=2.0)+
  geom_smooth(aes(y = y1),method=lm,se=FALSE,size=0.5,
              fullrange = TRUE)+ # Add regression line;
  annotate("text",x = 150,y =320, label = lm_eqn(lm(y1~x,df)), # maybe wrong
           size = 2.0, parse = TRUE)+ # Add regression line equation;
  
  geom_point(aes(y = y2),size=2.0)+
  geom_smooth(aes(y = y2),method=lm,se=FALSE,size=0.5,
              fullrange = TRUE)+ # Add regression line;
  annotate("text",x = 225,y =50, label = lm_eqn(lm(y2~x,df)),
           size = 2.0, parse = TRUE)+ # Add regression line equation;
  facet_wrap(~trt)

我的情节：

另外，在每个方面有两条线和你的方程，这两条线是对的，但这两个方程是错的。显然，左、右切面上的上/下方程应该彼此不同。

1）ggplot2首先尝试将

df

转换为长格式（请参见##行）。我们创建了一个注释数据框

ann

，它定义了文本，并将文本用于

geom_text

。请注意，由于绘图由

trt

分面，因此

geom_text

将使用

ann

的每行中的

trt

列将该行与适当的分面关联

library(ggplot2)
library(reshape2)

long <- melt(df, measure.vars = 2:3) ##

trts <- unique(long$trt)
ann <- data.frame(x = c(0, 100), 
                  y = c(250, 100), 
                  label = c(lm_eqn(lm(y1 ~ x, df, subset = trt == trts[1])), 
                            lm_eqn(lm(y2 ~ x, df, subset = trt == trts[1])),
                            lm_eqn(lm(y1 ~ x, df, subset = trt == trts[2])), 
                            lm_eqn(lm(y2 ~ x, df, subset = trt == trts[2]))),
                  trt = rep(trts, each = 2),
                  variable = c("y1", "y2"))

ggplot(long, aes(x, value)) +
       geom_point() + 
       geom_smooth(aes(col = variable), method = "lm", se = FALSE,
              full_range = TRUE) + 
       geom_text(aes(x, y, label = label, col = variable), data = ann, 
             parse = TRUE, hjust = -0.1, size = 2) +
       facet_wrap(~ trt)

（图后续）

2）lattice在这种情况下，使用lattice可能更容易：

library(lattice)

xyplot(y1 + y2 ~ x | factor(trt), df, 
       key = simpleKey(text = c("y1", "y2"), col = c("blue", "red")),
       panel = panel.superpose, 
       panel.groups = function(x, y, group.value, ...) {
          if (group.value == "y1") {
              X <- 150; Y <- 300; col <- "blue"
          } else {
              X <- 250; Y <- 100; col <- "red"
          }
          panel.points(x, y, col = col)
          panel.abline(lm(y ~ x), col = col)
          panel.text(X, Y, parse(text = lm_eqn(lm(y ~ x))), col = col, cex = 0.7)
       }
)

更新

• 添加了彩色文本
• 添加了备选

  ann

• 添加晶格解
• 向晶格解决方案添加晶格额外的变化

---

谢谢您的快速回复，但您的解决方案不适合我的问题。我想做的是在每个方面添加两条回归线和方程。我已经用一个数字更新了我的问题。那么我们应该在绘图之前准备好方程式吗？有没有办法自动完成准备工作？顺便问一下，如何将

geom_文本

设置为与

geom_平滑

相同的颜色？非常感谢。更新答案，为方程式添加颜色，并为

ann

提供替代等效表达式。

f <- function(v) lm_eqn(lm(value ~ x, long, subset = variable==v[[1]] & trt==v[[2]]))
Grid <- expand.grid(variable = c("y1", "y2"), trt = trts)
ann <- data.frame(x = c(0, 100), y = c(250, 100), label = apply(Grid, 1, f), Grid)

library(lattice)

xyplot(y1 + y2 ~ x | factor(trt), df, 
       key = simpleKey(text = c("y1", "y2"), col = c("blue", "red")),
       panel = panel.superpose, 
       panel.groups = function(x, y, group.value, ...) {
          if (group.value == "y1") {
              X <- 150; Y <- 300; col <- "blue"
          } else {
              X <- 250; Y <- 100; col <- "red"
          }
          panel.points(x, y, col = col)
          panel.abline(lm(y ~ x), col = col)
          panel.text(X, Y, parse(text = lm_eqn(lm(y ~ x))), col = col, cex = 0.7)
       }
)

library(latticeExtra)

xyplot(y1 + y2 ~ x | factor(trt), df, par.settings = ggplot2like(),
       key = simpleKey(text = c("y1", "y2"), col = c("blue", "red")),
       panel = panel.superpose, 
       panel.groups = function(x, y, group.value, ...) {
          if (group.value == "y1") {
              X <- 150; Y <- 300; col <- "blue"
          } else {
              X <- 250; Y <- 100; col <- "red"
          }
          panel.points(x, y, col = col)
          panel.grid()
          panel.abline(lm(y ~ x), col = col)
          panel.text(X, Y, parse(text = lm_eqn(lm(y ~ x))), col = col, cex = 0.7)
       }
)

df <-
structure(list(x = c(22.48349, 93.52976, 163.00984, 205.62072, 
265.46812, 23.79859, 99.97307, 189.91814, 268.1006, 325.65609, 
357.59726), y1 = c(34.2, 98.5, 164.2, 216.7, 271.8, 35.8, 119.4, 
200.8, 279.5, 325.7, 353.6), y2 = c(31, 96, 169.8, 210, 258.5, 
24.2, 90.6, 189.3, 264.6, 325.4, 353.8), trt = c(6030L, 6030L, 
6030L, 6030L, 6030L, 6060L, 6060L, 6060L, 6060L, 6060L, 6060L
)), .Names = c("x", "y1", "y2", "trt"), class = "data.frame", row.names = c(NA, 
-11L))