我想尽可能将nlsfit package中的easynls与ggplot2一起使用。
到目前为止，这是我所做的：
设置子集数据：
library('ggplot2')
library('easynls')
x <- seq(25,97)
y <- c(0.014, 0.016, 0.015, 0.016, 0.018, 0.019, 0.023, 0.019, 0.021, 0.017, 0.018, 0.016, 0.016, 0.020, 0.018, 0.019, 0.022, 0.023, 0.027, 0.027, 0.028, 0.031, 0.029, 0.032, 0.030, 0.030, 0.030, 0.033, 0.039, 0.038, 0.039, 0.046, 0.042, 0.043, 0.050, 0.054, 0.059, 0.064, 0.062, 0.058, 0.063, 0.069, 0.071, 0.069, 0.073, 0.071, 0.070, 0.077, 0.086, 0.077, 0.090, 0.086, 0.098, 0.108, 0.112, 0.116, 0.129, 0.120, 0.128, 0.141, 0.150, 0.143, 0.148, 0.150, 0.162, 0.162, 0.168, 0.152, 0.151, 0.161, 0.169, 0.189, 0.184)
data <- data.frame(x,y)
对样本数据运行NLSfit
nlsfit = nlsfit(data.frame(x,y), model=6, start=c(250,0.05))
nlsfit
# $Model
# [1] "y~a*exp(b*x)"
# $Parameters
# y
# coefficient a 0.0061
# coefficient b 0.0358
# p-value t.test for a 0.0000
# p-value t.test for b 0.0000
# r-squared 0.9793
# adjusted r-squared 0.9790
# AIC -500.0812
# BIC -493.2098
用
plot()画一条线plot(x, y)
a <- nlsfit$Parameters[1,]
b <- nlsfit$Parameters[2,]
lines(x, a*exp(x*b), col="steelblue")
尝试将
nls与ggplot2一起使用（此方法有效-但是在整个数据集中拟合度不佳）...ggplot(data, aes(x=x, y=y)) + geom_point(
) + geom_smooth(method="nls", formula=y~a*exp(x*b),
method.args=list(start=c(a=250,b=0.05)), se=FALSE)
用ggplot2尝试
nlsfit-不起作用# Below doesn't work
ggplot(data, aes(x=x, y=y)) + geom_point(
) + geom_smooth(method="nlsfit", formula=y~a*exp(x*b),
method.args=list(data.frame(x, y),
model=6, start=c(250,0.05)), se=FALSE)
# Warning message:
# Computation failed in `stat_smooth()`:
# unused arguments (formula, weights = weight, list(x = 25:97, y = c(0.014, 0.016, 0.015, 0.016, 0.018, 0.019, 0.023, 0.019, 0.021, 0.017, 0.018, 0.016, 0.016, 0.02, 0.018, 0.019, 0.022, 0.023, 0.027, 0.027, 0.028, 0.031, 0.029, 0.032, 0.03, 0.03, 0.03, 0.033, 0.039, 0.038, 0.039, 0.046, 0.042, 0.043, 0.05, 0.054, 0.059, 0.064, 0.062, 0.058, 0.063, 0.069, 0.071, 0.069, 0.073, 0.071, 0.07, 0.077, 0.086, 0.077, 0.09, 0.086, 0.098, 0.108, 0.112, 0.116, 0.129, 0.12, 0.128, 0.141, 0.15, 0.143, 0.148, 0.15, 0.162,
# 0.162, 0.168, 0.152, 0.151, 0.161, 0.169, 0.189, 0.184)))
这有可能吗？将不胜感激。谢谢。
最佳答案
您可以尝试stat_function使最后一部分起作用：
a <- nlsfit$Parameters[row.names(nlsfit$Parameters) == 'coefficient a',]
b <- nlsfit$Parameters[row.names(nlsfit$Parameters) == 'coefficient b',]
ggplot(data, aes(x=x, y=y)) + geom_point() +
stat_function(fun=function(x) a*exp(b*x), colour = "blue")
关于r - 在geom_smooth中使用`nlsfit`以添加指数线来绘制，我们在Stack Overflow上找到一个类似的问题：https://stackoverflow.com/questions/41881329/