我使用了来自R质量包的fitdistr函数来调整Weibull 2参数的概率密度函数。
这是我的密码:
require(MASS)
h = c(31.194, 31.424, 31.253, 25.349, 24.535, 25.562, 29.486, 25.680, 26.079, 30.556, 30.552, 30.412, 29.344, 26.072, 28.777, 30.204, 29.677, 29.853, 29.718, 27.860, 28.919, 30.226, 25.937, 30.594, 30.614, 29.106, 15.208, 30.993, 32.075, 31.097, 32.073, 29.600, 29.031, 31.033, 30.412, 30.839, 31.121, 24.802, 29.181, 30.136, 25.464, 28.302, 26.018, 26.263, 25.603, 30.857, 25.693, 31.504, 30.378, 31.403, 28.684, 30.655, 5.933, 31.099, 29.417, 29.444, 19.785, 29.416, 5.682, 28.707, 28.450, 28.961, 26.694, 26.625, 30.568, 28.910, 25.170, 25.816, 25.820)
weib = fitdistr(na.omit(h),densfun=dweibull,start=list(scale=1,shape=5))
hist(h, prob=TRUE, main = "", xlab = "x", ylab = "y", xlim = c(0,40), breaks = seq(0,40,5))
curve(dweibull(x, scale=weib$estimate[1], shape=weib$estimate[2]),from=0, to=40, add=TRUE)现在,我想创建Weibull累积分布函数,并将其绘制成一个图:

,其中x> 0,b=刻度,a=形状
我试图使用上面的公式为h应用缩放和形状参数,但情况并非如此。
发布于 2013-04-18 21:41:14
这里是一个累积密度函数的尝试。您只需记住包括对取样点间距的调整(注意:它适用于均匀间距小于或等于1的取样点):
cdweibull <- function(x, shape, scale, log = FALSE){
dd <- dweibull(x, shape= shape, scale = scale, log = log)
dd <- cumsum(dd) * c(0, diff(x))
return(dd)
}尽管上面对比例差异的讨论,您仍可以将其绘制在与dweibull相同的图形上。
require(MASS)
h = c(31.194, 31.424, 31.253, 25.349, 24.535, 25.562, 29.486, 25.680,
26.079, 30.556, 30.552, 30.412, 29.344, 26.072, 28.777, 30.204,
29.677, 29.853, 29.718, 27.860, 28.919, 30.226, 25.937, 30.594,
30.614, 29.106, 15.208, 30.993, 32.075, 31.097, 32.073, 29.600,
29.031, 31.033, 30.412, 30.839, 31.121, 24.802, 29.181, 30.136,
25.464, 28.302, 26.018, 26.263, 25.603, 30.857, 25.693, 31.504,
30.378, 31.403, 28.684, 30.655, 5.933, 31.099, 29.417, 29.444,
19.785, 29.416, 5.682, 28.707, 28.450, 28.961, 26.694, 26.625,
30.568, 28.910, 25.170, 25.816, 25.820)
weib = fitdistr(na.omit(h),densfun=dweibull,start=list(scale=1,shape=5))
hist(h, prob=TRUE, main = "", xlab = "x",
ylab = "y", xlim = c(0,40), breaks = seq(0,40,5), ylim = c(0,1))
curve(cdweibull(x, scale=weib$estimate[1], shape=weib$estimate[2]),
from=0, to=40, add=TRUE)

发布于 2013-03-09 00:09:02
这适用于我的数据,但你的可能不一样。它使用来自rweibull3包的FAdist函数。
>h=rweibull3(1000,2,2,2)
>#this gives some warnings...that I ignore.
>weib = fitdistr(h,densfun=dweibull3,start=list(scale=1,shape=5,thres=0.5))
There were 19 warnings (use warnings() to see them) 需要注意的是,起始值会影响匹配的进行方式。因此,如果开始值接近真值,则会收到较少的警告。
>curve(dweibull3( x,
scale=weib$estimate[1],
shape=weib$estimate[2],
thres=weib$estimate[3]),
add=TRUE)

https://stackoverflow.com/questions/15303310
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