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"?

Respuestas (1)

Satwik Samayamantry
Satwik Samayamantry el 14 de Jul. de 2023
Hi Sim,
Yeah you got it right. Your understanding for both cases is correct.

3 comentarios

Sim
Sim el 1 de Ag. de 2023
Editada: Sim el 1 de Ag. de 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 el 1 de Ag. de 2023
thanks @Steven Lord :-)

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Sim
el 14 de Jul. de 2023

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Sim
el 1 de Ag. de 2023

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