Fiting for normalized histrogram.

Hi

I want to make a fit for my histogram that is normalized. The histfit function does not seem to normalize with probability. Can somebody help me fit the histogram written below?

step = 1000; % Shows the number of steps

P = zeros(step,1);

x = [1:10000];

added = 0;

d = 0;

for i=1:10000 %The simulation repeats for 100,000 times

added = 0;

for j=2:step

R = rand;

if R < 0.5

S = -1;

elseif R > 0.5

S = 1;

end

P(j) = S+P(j-1);

end

x(i) = P(length(P));

added = added + x(i);

end

histogram(x,'Normalization','probability');

Answer 1

[Star Strider]

Divide the ‘Bar’ object and the ‘Line’ object by thier maximum values:

figure
hfh = histfit(x);
hfh(1).YData = hfh(1).YData/max(hfh(1).YData);
hfh(2).YData = hfh(2).YData/max(hfh(2).YData);

That should produce the result you want.

Answer 2

[Pradeesh]

You may follow the documentation to use the following function for fitting normalized histogram for which a sample fit for normalized histogram is provided.

fitdist