From: Mehdi bahonar on 13 Mar 2010 03:47 Hi There, Do you know how we can convert histogram plot to probability density function plot? Thanks, maryam
From: Ulf Graewe on 13 Mar 2010 04:18 "Mehdi bahonar" <mehdiuoc(a)yahoo.com> wrote in message <hnfji1$sko$1(a)fred.mathworks.com>... > Hi There, > > Do you know how we can convert histogram plot to probability density function plot? > > Thanks, > maryam maybe you have to normalise the histogram, so that the probability to be in the total interval is 1. a first hint: doc trapz
From: Sadik on 13 Mar 2010 06:03 a = randn(1,10000); [n,x] = hist(a,50); plot(x,n/10000/diff(x(1:2))) hold on plot(x,normpdf(x,0,1),'r') Therefore, n/10000/diff(x(1:2)) is your pdf. [diff(x(1:2)) looks at deltaX, that is bin width.] "Mehdi bahonar" <mehdiuoc(a)yahoo.com> wrote in message <hnfje9$r0d$1(a)fred.mathworks.com>... > Hi There, > > Do you know how we can convert histogram plot to probability density function plot? > > Thanks, > maryam
From: Wayne King on 13 Mar 2010 10:44 "Mehdi bahonar" <mehdiuoc(a)yahoo.com> wrote in message <hnfje9$r0d$1(a)fred.mathworks.com>... > Hi There, > > Do you know how we can convert histogram plot to probability density function plot? > > Thanks, > maryam Hi maryam, if you have the Statistics Toolbox, histfit() will superimpose a probability density function for a number of distributions. Wayne
From: the cyclist on 13 Mar 2010 15:43 "Mehdi bahonar" <mehdiuoc(a)yahoo.com> wrote in message <hnfje9$r0d$1(a)fred.mathworks.com>... > Hi There, > > Do you know how we can convert histogram plot to probability density function plot? > > Thanks, > maryam As has been mentioned, use HISTFIT if you know the underlying distribution type that you want to fit (e.g. normal distribution). If you do not, then you need to do a non-parametric fit. You can use the KSDENSITY function to do this. Note that this is a bit of an art in addition to science. You might want to read up on "kernel density estimation".
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