[英]Plotting fitted and original data in R, with higher density of x values for fitted
[英]R: Plotting fitted model with the confident intervals for each predicted values in x
如何為每個預測值(以x = 5、10、15、20、25、30、35)的置信區間繪制擬合模型?
對於下一個數據集
df<-data.frame(
x = rep(c( 5, 10, 15, 20, 25, 30, 35), each=4 ),
y = c(0.2, 1.1, 1.5, 0.9,
2.1, 1.9, 2.75, 3.4,
5.15, 4.6, 4.75, 4.15,
7, 6.7, 6.7, 6.95,
7, 5.45, 6.15, 6.4,
0.001, 0.001, 0.5,
0.001, 0.001, 0.001, 0.001, 0.001)
)
head(df)
以及以下擬合模型:
fun <-with(df,
y ~ Yopt*((x-Tmin)/(Topt-Tmin))^(b1*(Topt-Tmin)/(Tmax-Topt))*((Tmax-x)/(Tmax-Topt))^b1
)
starters <- expand.grid(Yopt = seq(4, 8, len = 4),
Tmin = seq(0, 5, len = 4),
Topt = seq(15, 25, len = 4),
Tmax= seq(28, 38, len = 4),
b1 = seq(0, 4, len = 4))
fit <- nls2(fun, start = starters, algorithm = "brute-force")
summary(fit)
with(df, c(plot(y~x))); points(fitted(fit)~I(df$x), pch=19)
with(as.list(coef(fit)),
curve(
Yopt*((x-Tmin)/(Topt-Tmin))^(b1*(Topt-Tmin)/(Tmax-Topt))*((Tmax-x) / (Tmax-Topt)) ^ b1,
add=TRUE, col="red"))
您應該認真對待@Roland對您對with
的使用的評論。
這樣做有更好的方法,但是在您的代碼上,我會做類似的事情。
library(ggplot2)
library(reshape2)
df$fitted <- fitted(fit)
df$upper <- df$fitted + 1 #I didn't bother to produce actual confidence band
df$lower <- df$fitted - 1
df <- melt(data = df, id.vars = c("x","upper","lower"))
coef <- coef(fit)
fit.fun <-function(x) coef[1]*((x-coef[2])/(coef[3]-coef[2]))^(coef[5]*(coef[3]-coef[2])/(coef[4]-coef[3]))*((coef[4]-x) / (coef[4]-coef[3])) ^ coef[5]
ggplot(df, aes(x=x)) + geom_point( aes(y=value, color=variable)) +
geom_segment(aes(x=x, xend=x, y=upper, yend=lower)) +
stat_function(fun=fit.fun, color="blue")
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