# I am trying to plot poisson density fit to my data x. but it doesnt seem to give the right results

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Judith Hershko on 11 Feb 2021
Answered: Shubham Khatri on 21 Feb 2021
%y is seconds
y=[20 50 100 200];
%x1 counts after 20s,x2 couns after 50s, x3 counts after 100s, x4 counts after
%200s
x1=[47 59 56 56 61 54 72 64 53 73 59 62 43 61 63 70 55 59 70 52 62 76 64 68 63];
x2=[129 167 139 154 154 171 167 132 151 139];
x3=[317 297 301 312 329];
x4=[612 598];
%x is detections per second
x=[x1/y(1) x2/y(2) x3/y(3) x4/y(4)]';
% Set seed for reproducibility
rng default
% Fit a poisson distribution
pd = fitdist(x,'poisson');
% Calculate the theoretical PDF from the fit parameters
x_range = 2:3.8;
probability_predicted = pdf(pd,x_range);
% Plot histogram and fit
figure
histogram(x,9)
xlabel('Observation');
ylabel('Probability');
h = plot(x_range,probability_predicted,'-');
set(h,'MarkerSize',24)
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Jeff Miller on 13 Feb 2021
Not sure if this will help, but...The normal distribution is a model for continuous numerical measurements that can take on any values. The Poisson is a model for counts, which have to be 0, 1, 2, 3, ...
Judith Hershko on 13 Feb 2021
Oh yes that helps a lot actually! Thank you so much!

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### Answers (1)

Shubham Khatri on 21 Feb 2021
Hello,
It didnt work because Poisson distribution is a discrete probability distribution of the number of events occurring in a given time period, given the average number of times the event occurs over that time period. It would be good if you can share your data source to find a good fit of a model.
Hope it helps
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