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Asked by Mate 2u
on 19 Feb 2012

Hi everybody. I have an array.

1) I do a histfit(data) to get a histogram representation of my data with a normal distribution curve on top. I want a 3rd thing on this graph and that is a smooth line representing the data (so I want the curve representing the distribution of my data on top of this to compare with the normal distribution)

Thanks.

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Answer by Tom Lane
on 19 Feb 2012

Accepted answer

There is a ksdensity function that can produce a kernel-smooth density estimate. The issue is that it produces a density (integrates to 1) and the histogram is not a density (bar heights sum to 1). You could figure out the area of the histogram and re-scale the ksdensity values. Alternatively, here's a way to create the histgram, normal curve, and kernel density separately:

x = [randn(100,1); 4+randn(50,1)]; [hts,ctrs] = hist(x) bar(ctrs,hts,'hist') area = sum(hts) * (ctrs(2)-ctrs(1)) xx = linspace(-3,7); hold on; plot(xx,area*normpdf(xx,mean(x),std(x)),'r-') f = ksdensity(x,xx); plot(xx,area*f,'g-') hold off

tiago
on 11 Sep 2013

Hi, thanks a lot for the help with the code There is any way to know the r^2 of the normal curve?

Thanks in advance

Tom Lane
on 11 Sep 2013

The normal curve is computed from the raw data, which is one-dimensional rather than the two-dimensional x/y data normally associated with R^2. So while maybe you could make something up related to the bar heights and the density values, I don't think there is a good way to apply R^2 here.

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