R与正常情形下的多图形化

时间:2012-11-14 03:34:16

标签: r graph distribution

我试图用正常曲线绘制实验数据(用于比较)。我可以很好地绘制其中一条曲线,但正常的曲线无法正确绘制,我只能在屏幕上看到一条线。我对dcauchy得到了相同的结果。正确绘制的唯一曲线是“pdf_cauchy”变量。

这就是我想要做的事情:

plot(pdf_cauchy, type = "l", col = "red", lwd = 4)
curve(dnorm(x, 0, 1), add = T, col = "blue", lwd = 4)
x <- seq(-5, 5, by = .001)
lines(dcauchy(x, 0, 1, FALSE), type = "l", col = "green", lwd = 4)

以下是“pdf_cauchy”

中的数据
c(0.00127277, 0.00132412, 0.0013786, 0.00143646, 0.00149797, 
0.00156345, 0.00163324, 0.00170772, 0.00178731, 0.00187247, 0.00196372, 
0.00206165, 0.00216691, 0.00228022, 0.00240241, 0.00253439, 0.0026772, 
0.00283202, 0.00300018, 0.00318319, 0.00338278, 0.0036009, 0.0038398, 
0.00410205, 0.00439061, 0.00470887, 0.00506072, 0.00545067, 0.00588391, 
0.00636639, 0.00690497, 0.00750753, 0.00818301, 0.00894155, 0.00979444, 
0.010754, 0.0118334, 0.0130459, 0.0144036, 0.015916, 0.0175867, 
0.0194097, 0.0213637, 0.0234058, 0.0254655, 0.0274413, 0.0292036, 
0.0306076, 0.0315168, 0.0318319, 0.0315168, 0.0306076, 0.0292036, 
0.0274413, 0.0254655, 0.0234058, 0.0213637, 0.0194097, 0.0175867, 
0.015916, 0.0144036, 0.0130459, 0.0118334, 0.010754, 0.00979444, 
0.00894155, 0.00818301, 0.00750753, 0.00690497, 0.00636639, 0.00588391, 
0.00545067, 0.00506072, 0.00470887, 0.00439061, 0.00410205, 0.0038398, 
0.0036009, 0.00338278, 0.00318319, 0.00300018, 0.00283202, 0.0026772, 
0.00253439, 0.00240241, 0.00228022, 0.00216691, 0.00206165, 0.00196372, 
0.00187247, 0.00178731, 0.00170772, 0.00163324, 0.00156345, 0.00149797, 
0.00143646, 0.0013786, 0.00132412, 0.0012

2 个答案:

答案 0 :(得分:3)

考虑这些图中你的x轴是什么。您的初始绘图没有给出x轴,因此只使用1:100作为100 Cauchy值。现在你添加一条正常的曲线,从0开始,然后变为100,平均值为0.你只能获得曲线的右半部分和极值。平均值为50,sd为25,你会得到更合理的东西,你也可以用dcauchy做类似的事情。

你可能真的需要在初始情节中加入一些x值,但我不知道它们是什么。您是否希望展示位置的峰值为0?...其他一些值?只有你知道x轴的位置和范围应该是什么。

答案 1 :(得分:0)

这是一个很好的绘图方式:

plot(x, dcauchy(x, 0, 1, FALSE), type = "l", col = "red", lwd = 4)
par(new = TRUE)
plot(x, pdf_cauchy, type = "l", col = "blue", lwd = 2)
par(new = TRUE)
plot(x, dnorm(x, 0, 1), type = "l", col = "green", lwd = 3)