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Questions tagged [bhattacharyya]

Use this tag if you are asking about the Bhattacharyya distance or the Bhattacharyya coefficient.

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Bhattacharyya distance and KL divergence show contradicting behavior

Bhattacharyya distance between two distributions $p$ and $q$ is defined as $D_B(p,q)=-\log(\int\sqrt{p(x)q(x)})dx$, The KL-divergence is defined as $D_{kl}(p||q)=\int p(x)\log(\frac{p(x)}{q(x)})dx$. ...
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Intuition of the Bhattacharya Coefficient and the Bhattacharya distance?

The Bhattacharyya distance is defined as $D_B(p,q) = -\ln \left( BC(p,q) \right)$, where $BC(p,q) = \sum_{x\in X} \sqrt{p(x) q(x)}$ for discrete variables and similarly for continuous random variables....
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Measuring the similarity of two distributions

What is the recommended approach to measure the similarity between two distributions of a variable—discrete and continuous? Is Bhattacharyya distance a good measure?
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Is it correct to compute Bhattacharyya distance for Cauchy like, Bell shaped function?

I have the algorithm (MF (Membership function) ARTMAP Neural network). Output from this algorithm are clusters in n-dimensional feature space. Over each cluster (in n+1 dimension) there is some ...
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distance measure of two discrete probability histograms (distance between two vectors)

I have multiple sets of discrete probability histograms(vectors) and I want to measure the distance between each histogram. I have done some research but I am in doubt. Literature suggest I could ...
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Can I use the Bhattacharyya distance as an acceptance criterion for Approximate Bayesian Computation?

I am researching the spread of a disease through a population and want to capture the behavior of this disease with a model. I already have a model and patient data. The data is a value per patient ...
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Does maximal Bhattacharyya coefficient imply mimimal total variation distance?

I'm working on numerical optimization (linear programming), on probability distributions denoted P, Q. We want to find the minimal total variation distance and maximal Bhattacharyya coefficient ...
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Bhattacharya Distance on Distributions (Matrices) with Different Number of Variables (Dimensions) [duplicate]

We have two matrices, $A$ and $B$, representing two different probability distributions, with dimensions, $m*n$ and $k*n$, respectively. How can we calculate the Bhattacharya distance or another ...
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Bhattacharyya Distance for Age/Gender Groups?

I'm calculating distances for groups based on Age/Gender Compositions (to rank their similarity in demographic composition.) I'm working with the following: Men 18-34, Men 35-49, Men 50-64, Men 65+, ...
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Differences between Bhattacharyya distance and KL divergence

I'm looking for an intuitive explanation for the following questions: In statistics and information theory, what's the difference between Bhattacharyya distance and KL divergence, as measures of the ...
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Normalize vector-based integer data

I'll preface my question by saying I have a very limited knowledge of statistics, and while I've put some thought into this problem, I'm a bit stuck! Onwards... I have a collection of fixed-size ...
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Statistical distance tests

I am using around 200 variables to compare 2 populations, group A and group B. Here's a representation of what the data looks like ...
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Bhattacharyya distance for three histograms

There is a paper “Auto White Balance Based on the Similarity of Chromaticity Histograms” mention about automatic white balance. One of the key point of this algorithm is how to measure the similarity ...
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Statistical Distance Within Multivariate Distribution

Suppose you have some multivariate normal distribution $X \sim N(\mu,\Sigma)$. Is there a good way to calculate a measure of distance between an arbitrary $X_{i}$ and $X_{j}$ of $X$ (I suppose the ...
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Bhattacharyya distance for histograms

One of the ways to measure the similarity of two discrete probability distributions is the Bhattacharyya distance. In computer vision, for example, it is used to evaluate the degree of similarity ...
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Percentage of overlapping regions of two normal distributions

I was wondering, given two normal distributions with $\sigma_1,\ \mu_1$ and $\sigma_2, \ \mu_2$ how can I calculate the percentage of overlapping regions of two distributions? I suppose this problem ...