R
包ggpmisc
可用于在lm
(See here上显示poly
模型和ggplot2
模型的等式以供参考。想知道如何使用nls
在ggplot2
上显示ggmisc
模型方程式结果。以下是我的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)
答案 0 :(得分:4)
受到您关联的帖子的启发。在提取参数后使用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)
答案 1 :(得分:0)
在这里,我使用当前的 CRAN ggpmisc (v 0.3.8) 展示了使用 ggpmisc 添加到图中的组的 nls。这是小插图的变体/修改,其中 'stat_fit_tidy()' 使用了 michaelis-menten 拟合,发现 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")