如何在 R 中为我的数据拟合平滑曲线? [英] How to fit a smooth curve to my data in R?

问题描述

我正在尝试在 R 中绘制平滑曲线.我有以下简单的玩具数据:

I'm trying to draw a smooth curve in R. I have the following simple toy data:

> x
 [1]  1  2  3  4  5  6  7  8  9 10
> y
 [1]  2  4  6  8  7 12 14 16 18 20

现在，当我使用标准命令绘制它时，它看起来很颠簸和前卫，当然:

Now when I plot it with a standard command it looks bumpy and edgy, of course:

> plot(x,y, type='l', lwd=2, col='red')

如何使曲线平滑，以便使用估计值使 3 条边变圆?我知道有很多方法可以拟合平滑曲线，但我不确定哪种方法最适合这种类型的曲线，以及如何在 R 中编写它.

How can I make the curve smooth so that the 3 edges are rounded using estimated values? I know there are many methods to fit a smooth curve but I'm not sure which one would be most appropriate for this type of curve and how you would write it in R.

推荐答案

我非常喜欢 loess() 用于平滑:

I like loess() a lot for smoothing:

x <- 1:10
y <- c(2,4,6,8,7,12,14,16,18,20)
lo <- loess(y~x)
plot(x,y)
lines(predict(lo), col='red', lwd=2)

Venables 和 Ripley 的 MASS 书有一整节关于平滑，也涵盖了样条和多项式——但 loess() 几乎是每个人的最爱.

Venables and Ripley's MASS book has an entire section on smoothing that also covers splines and polynomials -- but loess() is just about everybody's favourite.

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