试图用ggplot2的geom_smooth（）显示原始数据和拟合数据（nls + dnorm）
我正在探索一些数据，所以我想要做的第一件事就是尝试将正态（高斯）分布拟合到它。这是我第一次在R中尝试这个，所以我一步一步。首先我预先分类我的数据：
myhist = data.frame(size = 10:27, counts = c(1L, 3L, 5L, 6L, 9L, 14L, 13L, 23L, 31L, 40L, 42L, 22L, 14L, 7L, 4L, 2L, 2L, 1L) )
qplot(x=size, y=counts, data=myhist)
fit = nls(counts ~ N * dnorm(size, m, s), data=myhist, start=c(m=20, s=5, N=sum(myhist$counts)) )
x = seq(10,30,0.2)
fitted = data.frame(size = x, counts=predict(fit, data.frame(size=x)) )
ggplot(data=myhist, aes(x=size, y=counts)) + geom_point() + geom_line(data=fitted)
ggplot(data=myhist, aes(x=size, y=counts)) + geom_point() + geom_smooth(method="nls", formula = counts ~ N * dnorm(size, m, s), se=F, start=list(m=20, s=5, N=300, size=10))
Error in method(formula, data = data, weights = weight, ...) :
parameters without starting value in 'data': counts
fitting parameters ‘m’, ‘s’, ‘N’, ‘size’, ‘counts’ without any variables
Error in eval(expr, envir, enclos) : object 'counts' not found
没有找到相关结果
已邀请:
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雄鞋谋塘
ggplot(data=myhist, aes(x=size, y=counts)) + geom_point() + geom_smooth(method="nls", formula = y ~ N * dnorm(x, m, s), se=F, start=list(m=20, s=5, N=300))