Normalize histogram of normally distributed data

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Bernoulli Lizard
Bernoulli Lizard 2013-3-12
How can I normalize a histogram of normally distributed points? I have tried using histnorm from the file exchange and a few other suggestions in the help forums, but the height of my bins are on the order of 10^4.
I am using normrand to distribute data points, but the height of the histogram (or height of the pdf when I use histfit) always depends upon the number of data points and the number of bins I use.
Thanks

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回答（2 个）

Honglei Chen
Honglei Chen 2013-3-12
You just need to normalize it toward the number of points
x = randn(1024,1)
[n,b] = hist(x)
bar(b,n/sum(n))
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Bernoulli Lizard
Bernoulli Lizard 2013-3-13
No, because then the height still depends upon the number of bins
Honglei Chen
Honglei Chen 2013-3-13
编辑：Honglei Chen 2013-3-14
Then what is your rule of normalization, normalize towards what?

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Tom Lane
Tom Lane 2013-3-14
I would normalize it to area 1. The usual histogram has area equal to binwidth*sum(n), so divide by that. Probably binwidth=b(2)-b(1).
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显示 4更早的评论
Image Analyst
Image Analyst 2013-6-27
We can't run this - it says span is undefined. The histogram is a quantized PDF. You won't get the true PDF unless you have an infinite number of infinitely thin histogram bins. So of course the histogram changes as you change the bin width - you have a finite number of samples that are counted. And you can't get infinitely thin, infinitely many bins with digitized, discrete data because that's just how a computer works.
Peter Perkins
Peter Perkins 2013-6-27
You want to compare a histogram to a PDF. Tom's suggestion is the correct one. The histogram integrates to binwidth*numObservations, the PDF to 1. The easiest thing to do is to scale your PDF by multiplying by binwidth*numObservations, but you can also call hist, get the bin counts, normalize them by dividing by binwidth*numObservations, and call bar.
If your PDF is a fit to the data, I'd recommend plotting the data and fitting the model using the dfittool GUI, which makes the plot your looking for (as well as many others) automatically.
Hope this helps.

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