[英]How to change the appearance of the best fit line in R
我正在尝试添加多项式最佳拟合线,但由于某种原因,它似乎在绘图上来回绘制。 我想知道我应该怎么做才能修好这条线
yhat_pol = lm(age~poly(height,2), data = Loblolly)
yhat_lin = lm(age~height, data = Loblolly)
plot(x=Loblolly$height, y=Loblolly$age, pch=16, xlab = "Height (ft)", ylab = "Age (yr)", main = "Height vs Age of Loblloy Pine Trees")
lines(Loblolly$height, predict(yhat_pol), type="l", col="green", lwd=2)
lines(Loblolly$height, predict(yhat_lin), type="l", col="red", lwd=2)
lines(sort(Loblolly$height), fitted(yhat_lin)[order(Loblolly$height)])
legend("topleft",
legend = c("linear","polynomial"),
col = c("red","green"),
lty = 1, lwd=3)
高度 | 年龄 | 种子 | |
---|---|---|---|
1 | 4.51 | 3 | 301 |
15 | 10.89 | 5 | 301 |
29 | 28.72 | 10 | 301 |
43 | 41.74 | 15 | 301 |
57 | 52.70 | 20 | 301 |
71 | 60.92 | 25 | 301 |
2 | 4.55 | 3 | 303 |
16 | 10.92 | 5 | 303 |
30 | 29.07 | 10 | 303 |
44 | 42.83 | 15 | 303 |
你没有要求它,但这是 - 正如布赖恩蒙哥马利所指出的 - 一个使用ggplot2
的解决方案:
library(dplyr)
library(tidyr)
library(ggplot2)
Loblolly %>%
mutate(age_pred_pol = predict(yhat_pol),
age_pred_lin = predict(yhat_lin)) %>%
ggplot(aes(x = height, y = age)) +
geom_point() +
geom_line(aes(y = age_pred_pol, color = "Polynomial Best Fit")) +
geom_line(aes(y = age_pred_lin, color = "Linear Best Fit")) +
labs(x = "Height (ft)", y = "Age (yr)", title = "Height vs Age of Loblloy Pine Trees") +
scale_colour_manual(name = "Prediction",
breaks = c("Polynomial Best Fit", "Linear Best Fit"),
values = c("red", "green")) +
theme_bw()
这返回
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