如何在R中添加不同的趋势线？

Question

我知道如何使用lm和abline函数添加线性趋势线，但如何添加其他趋势线，例如对数，指数和功率趋势线？

Answer 1

这是我之前准备的：

# set the margins
tmpmar <- par("mar")
tmpmar[3] <- 0.5
par(mar=tmpmar)

# get underlying plot
x <- 1:10
y <- jitter(x^2)
plot(x, y, pch=20)

# basic straight line of fit
fit <- glm(y~x)
co <- coef(fit)
abline(fit, col="blue", lwd=2)

# exponential
f <- function(x,a,b) {a * exp(b * x)}
fit <- nls(y ~ f(x,a,b), start = c(a=1, b=1)) 
co <- coef(fit)
curve(f(x, a=co[1], b=co[2]), add = TRUE, col="green", lwd=2) 

# logarithmic
f <- function(x,a,b) {a * log(x) + b}
fit <- nls(y ~ f(x,a,b), start = c(a=1, b=1)) 
co <- coef(fit)
curve(f(x, a=co[1], b=co[2]), add = TRUE, col="orange", lwd=2) 

# polynomial
f <- function(x,a,b,d) {(a*x^2) + (b*x) + d}
fit <- nls(y ~ f(x,a,b,d), start = c(a=1, b=1, d=1)) 
co <- coef(fit)
curve(f(x, a=co[1], b=co[2], d=co[3]), add = TRUE, col="pink", lwd=2) 

添加描述性图例：

# legend
legend("topleft",
    legend=c("linear","exponential","logarithmic","polynomial"),
    col=c("blue","green","orange","pink"),
    lwd=2,
    )

结果：

绘制曲线的通用且不太长的方法是将x和系数列表传递给curve函数，如：

curve(do.call(f,c(list(x),coef(fit))),add=TRUE)

Answer 2

ggplot2方法使用stat_smooth，使用与thelatemail相同的数据

DF <- data.frame(x, y)



ggplot(DF, aes(x = x, y = y)) + geom_point() +
  stat_smooth(method = 'lm', aes(colour = 'linear'), se = FALSE) +
  stat_smooth(method = 'lm', formula = y ~ poly(x,2), aes(colour = 'polynomial'), se= FALSE) +
  stat_smooth(method = 'nls', formula = y ~ a * log(x) +b, aes(colour = 'logarithmic'), se = FALSE, start = list(a=1,b=1)) +
  stat_smooth(method = 'nls', formula = y ~ a*exp(b *x), aes(colour = 'Exponential'), se = FALSE, start = list(a=1,b=1)) +
  theme_bw() +
  scale_colour_brewer(name = 'Trendline', palette = 'Set2')

您还可以将指数趋势线拟合为使用glm和日志链接功能

glm(y~x, data = DF, family = gaussian(link = 'log'))

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为了获得一些乐趣，您可以使用ggthemes

中的theme_excel

library(ggthemes)
ggplot(DF, aes(x = x, y = y)) + geom_point() +
  stat_smooth(method = 'lm', aes(colour = 'linear'), se = FALSE) +
  stat_smooth(method = 'lm', formula = y ~ poly(x,2), aes(colour = 'polynomial'), se= FALSE) +
  stat_smooth(method = 'nls', formula = y ~ a * log(x) +b, aes(colour = 'logarithmic'), se = FALSE, start = list(a=1,b=1)) +
  stat_smooth(method = 'nls', formula = y ~ a*exp(b *x), aes(colour = 'Exponential'), se = FALSE, start = list(a=1,b=1)) +
  theme_excel() +
  scale_colour_excel(name = 'Trendline', palette = 'Set2')