Linked Questions

3
votes
1answer
2k views

Jeffries Matusita distance for 14 variables

I wish to perform Jeffries-Matusita distance on 14 spectral bands. Is there anyone who can help with how it is done in R? Thank you.
19
votes
1answer
978 views

Diagnostic plot for assessing homogeneity of variance-covariance matrices

Is there a handy plot for comparing the variance-covariance matrices of two (or perhaps more) groups? An alternative to looking at lots of marginal plots, especially in the multivariate Normal case?
4
votes
3answers
1k views

Is it feasible to use k-Nearest Neighbours to identify text language?

I have seen various language identification libraries that claim to use naive Bayes classifier for text language identification, like CLD2 and language detector, but not any library that uses other ...
3
votes
1answer
2k views

The derivation of the Mahalanobis distance formula [closed]

I recently asked about the Mahalanobis distance and I got pretty good answers in this post: Bottom to top explanation of the Mahalanobis distance? I think I got the idea, but what I still felt ...
12
votes
1answer
473 views

How to sample uniformly from the surface of a hyper-ellipsoid (constant Mahalanobis distance)?

In a real-valued multivariate case, is there a way to uniformly sample the points from the surface where the Mahalanobis distance from the mean of the is a constant? EDIT: This just boils down to ...
2
votes
1answer
2k views

Comparing two datasets

I'm not very familiar in statistics so please bear with me. I have two datasets which consist of four attributes: ...
1
vote
1answer
1k views

Dimensionality reduction for high dimensional sparse data before clustering or spherical k-means?

I am trying to build my first recommender system where i create a user feature space and then cluster them into different groups. Then for the recommendation to work for a particular user , first i ...
2
votes
1answer
1k views

Which error is displayed in an error ellipse?

I have some bivariate data and I have calculated the error ellipse in the following way: I have first calculated the covariance matrix and then to obtain the radii of the ellipse I have taken the ...
4
votes
2answers
439 views

Distance measure for binomial data

Assume a distribution for the normal data and test each point $\vec {x}[κ]$ for distance from the mean. A widely used distance measure is the Mahalanobis distance. If the data are not normal, but ...
3
votes
1answer
635 views

Probability that at least one sample lies within a given st.d.?

I think my question is similar to this one, but different in that I consider a set of realisations, not only one. Sorry if this question is really easy, I'm just not sure how to go rigorously about it....
2
votes
0answers
1k views

Mahalanobis Distance in Easy to Understand Pseudo Code

Conceptually I understand what's going on, some researchers use this as a heuristic for multi-variate outlier detection. I also get that we are measuring the distance of a data point from the mean in ...
2
votes
1answer
264 views

Physical significance: multiplying matrix by outer product of its eigenvector

I stumbled around this piece of code: v1 <- eigen(X.center %*% t(X.center))$vectors[,1] X.0 <- v1 %*% t(v1) %*% X.center while v1 is the eigenvector ...
3
votes
1answer
428 views

Inverse covariance matrix as linear transform

I'm trying to visualize the Mahalanobis distance $x^{t} \cdot Σ^{-1} \cdot x$ to get a better intuition. to do so, I assumed some data points from $N(0,1)$ and tried to plot $Σ^{-1} \cdot x$ to ...
6
votes
1answer
148 views

Multiplying vectors by the covariance matrix?

I thought I knew covariance but I'm starting to think that there's more to it. For example, what happens when you multiply observations by their corresponding covariance matrix? ...
1
vote
1answer
201 views

Mahalanobis distance gives counterintuitive results [closed]

I have generated 100 sample time series, each 24 items long, and each with an exponential distribution with a different scale for each of the 24 time points. This is the scale parameter per time point:...

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