Histogram

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.

Answer 1

[Tom Lane]

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]

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]

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.

Answer 2

[Jyoti Verma]

a=[4,5,1,2,2,3,4,2,2,1]

b=[4;5;1;2;2;3;4;2;2;1]

n=length(a);

RangeMax=max(a);

RangeMin=min(a);

sizehist=RangeMax-RangeMin+1;

histogram=zeros(sizehist,1);

for i=1:n

histogram(a(i))=histogram(a(i))+1;

end

bar(histogram);

Answer 3

[pavan kumar]

What is the procedure to find the Histogram coefficients?