Histogram normalisation: a question about terminology

Let's consider the histogram and histcounts functions, as in these two cases:
num_bins = 30; % <-- note: I specify the "number of bins" and not the "bin width", which can be different from 1
% Case 1
histcounts(X,num_bins,'Normalization','probability');
histogram(X,'NumBins',num_bins,'Normalization','probability');
% Case 2
histcounts(X,num_bins,'Normalization','pdf');
histogram(X,'NumBins',num_bins,'Normalization','pdf');
Do I understand correctly that
  1. For Case 1, I get the "Relative Frequency Histogram" or an "empirical estimate of the Probability Mass Function"?
  2. For Case 2, - where I divide by the bin widths as well -, I get the an "empirical estimate of the Probability Density Function"?

Réponses (1)

Satwik Samayamantry
Satwik Samayamantry le 14 Juil 2023

0 votes

Hi Sim,
Yeah you got it right. Your understanding for both cases is correct.

3 commentaires

Sim
Sim le 1 Août 2023
Modifié(e) : Sim le 1 Août 2023
Thanks for your comment @Satwik Samayamantry! Before accepting your answer, do you know/have some reference supporting your answer?
See the description of the Normalization name-value argument on either of the histogram or histcounts documentation pages. It describes exactly what the Values property of the histogram or the first output of the histcounts function represent.
Sim
Sim le 1 Août 2023
thanks @Steven Lord :-)

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Question posée :

Sim
le 14 Juil 2023

Commenté :

Sim
le 1 Août 2023

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