用ggpmisc显示nls模型的方程

Question

R软件包ggpmisc可用于在ggplot2上显示lm模型方程和poly模型方程(参考See here)。我想知道如何使用ggpmisc在ggplot2上显示nls模型方程结果。下面是我的MWE。

library(ggpmisc)
args <- list(formula = y ~ k * e ^ x,
             start = list(k = 1, e = 2))
ggplot(mtcars, aes(wt, mpg)) +
  geom_point() +
  stat_fit_augment(method = "nls",
                   method.args = args)

Answer 1

受到你链接的帖子的启发。提取参数后，使用geom_text添加标签。

nlsFit <-
  nls(formula = mpg ~ k * e ^ wt,
      start = list(k = 1, e = 2),
      data = mtcars)

nlsParams <-
  nlsFit$m$getAllPars()

nlsEqn <-
  substitute(italic(y) == k %.% e ^ italic(x), 
             list(k = format(nlsParams['k'], digits = 4), 
                  e = format(nlsParams['e'], digits = 2)))

nlsTxt <-
  as.character(as.expression(nlsEqn))

ggplot(mtcars, aes(wt, mpg)) +
  geom_point() +
  stat_fit_augment(method = "nls",
                   method.args = args) + 
  geom_text(x = 5, y = 30, label = nlsTxt, parse = TRUE)

Answer 2

在这里，我使用当前的CRAN ggpmisc (v0.3.8)显示了nls和使用ggpmisc添加到绘图中的组。这是片段的变体/修改，其中'stat_fit_tidy()‘使用michaelis-menten拟合，找到here。输出如下所示：

​

library(tidyverse)
library(tidymodels)
library(ggpmisc)

my_exp_formula <-  y ~ a * exp(b*x-0)
# if x has large values (i.e. >700), subtract the minimum
# see https://stackoverflow.com/a/41108403/4927395

#example with nls, shows the data returned
o <- nls(1/rate ~ a * exp(b*conc-0), data = Puromycin, start = list(a = 1, b = 2))
o
tidy(o)

ggplot(Puromycin, aes(conc, 1/rate, colour = state)) +
  geom_point() +
  geom_smooth(method = "nls", 
              formula = my_exp_formula,
              se = FALSE) +
  stat_fit_tidy(method = "nls", 
                method.args = list(formula = my_exp_formula),
                label.x = "right",
                label.y = "top",
                aes(label = paste("a~`=`~", signif(stat(a_estimate), digits = 3),
                                  "%+-%", signif(stat(a_se), digits = 2),
                                  "~~~~b~`=`~", signif(stat(b_estimate), digits = 3),
                                  "%+-%", signif(stat(b_se), digits = 2),
                                  sep = "")),
                parse = TRUE)
ggsave("exp plot.png")