MATLAB: Plot pdf from histogram – dice

dicediehistogrampdfprobabilityprobability density functionrandom

I set up my histogram:

AllRoll = randi(6,50000, 1);
SumRoll = sum(AllRoll, 2);
Bins = (1:6);
hist(SumRoll,Bins);
title(sprintf('Histogram'));
xlabel(sprintf('1-6'));
ylabel(sprintf('number of rolls'));
grid on
hold on

I'm trying to turn this into a pdf. I know I have to bring down the values so that it can equal 1, but I'm not sure what I'm dividing and multiplying and summing here.

Best Answer

hist function is not recommended. Please use histogram function instead.

And by setting the 'Normalization' option, PDF can be plotted, like:

AllRoll = randi(6,50000, 1);
SumRoll = sum(AllRoll, 2);
Edges = 0.5:1:6.5;
histogram(SumRoll,Edges,'Normalization','probability');
title(sprintf('PDF'));
xlabel(sprintf('1-6'));
ylabel(sprintf('Probability'));
grid on
hold on

Related Solutions

MATLAB: Normalized distribution for histogram

If you have the Statistics Toolbox, you might find the dfittool distribution fitting tool quite useful.

doc dfittool

If not, you can normalize a histogram by scaling the counts in each bin. With the normalized counts, you can plot both the normalized histogram and your curve. The trick is to identify the appropriate scaling factor.

Here is some example code where I plot the normal probability with the normalized histogram data:

% Arbitrary data generation and statistics
dataVec = randn(1000,1);
muData = mean(dataVec);
stdData = std(dataVec);
% Defining the bin centers
binStep    = 0.1;
binCenters = -5:binStep:5;
% Compute the histogram scaling factor. (If all histogram counts are in a
% single bin, the probability = 1)
binCount   = histc(dataVec,binCenters);
probScale  = sum(binCount)*binStep;
% Plot the normalized histogram and change the bar color for line
% visibility
histHandle = bar(binCenters,binCount/probScale,'hist');
set(histHandle,'FaceColor',[1,1,1]); 
hold on;
% Overlay the distribution fit on the histogram
x = binCenters;
y = normpdf(x,muData,stdData);
plot(x,y);
xlabel('Data');
ylabel('Probability');

Hope this helps to get you started!

MATLAB: For texture classification i have taken lbp as a feature..after applying lbp i have taken histogram..how to normalise the bins of histogram..and what is meant by normalise bins of histogram

Normalization would mean that you either divide by the max value of the counts, or that you divide by the sum of all the counts.

[pixelCounts grayLevels] = imhist(lbpImage, 256);
normalizedHist1 = pixelCounts / max(pixelCounts(:));
normalizedHist2 = pixelCounts / sum(pixelCounts(:));

It means that either the max value of any count will be 1.0, or that the sum of all counts would now be 1.0, depending on which method you use.

Best Answer

Related Solutions

MATLAB: Normalized distribution for histogram

MATLAB: For texture classification i have taken lbp as a feature..after applying lbp i have taken histogram..how to normalise the bins of histogram..and what is meant by normalise bins of histogram

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