Measure of distance between distributions or variables, such as Euclidean distance between points in n-space.

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Comparing Euclidean distances

I have 3 sets of values for X, Y & Z eg X = 7,8,7,8,6,9,8 Y = 8,7,7,6,7,8,8 Z = 8,8,8,7,8,9,9 I want compare the euclidean distance between these sets (X ...
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6 views

distances for partial rankings

I would like to know how I can compute the "Kendall distance" and the "Footrule distance" for partial rankings. I know only the general definitions for these distance that are exploitable only on full ...
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21 views

assumptions to compute mahalanobis distance

Which are the assumptions to compute the Mahalanobis distance between two groups? Do all the variables of the two groups be normal distributed?
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32 views

Doubt with a distance based Redundancy analysis

I conducted a distance based redundancy analysis (dbRDA) to explore the relevance of some environmental variables in explaining the patterns of the distribution (i.e., spatial and temporal) of two ...
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27 views

Distances in PCA space

I'm working on a project involving PCA, and my knowledge up till now with this method is quite good. My work involves finding nearest neighbors (having the least Euclidean distance) to a particular ...
6
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102 views

Efficient way to compute distances between centroids from distance matrix

Let us have square symmetric matrix of squared euclidean distances $\bf D$ between $n$ points and vector lengthed $n$ indicating cluster or group membership ($k$ clusters) of the points; a cluster may ...
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118 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 ...
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42 views

k means with binary variables

Is it OK to use kmeans with binary variables? I mean Euclidean distance? I guess the binary variables will be the ones that get the most power to determine the ...
4
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46 views

Cholesky factorization and forward substitution less accurate than inversion?

I recently asked this question asking for an efficient way to compute the Mahalanobis distance (without calculating the inverse). The accepted solution was to use the Cholesky factorization and ...
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242 views

Efficient/fast Mahalanobis distance computation

Suppose I have $n$ data points $x_1,\dots,x_n$, each of which is $p$-dimensional. Let $\Sigma$ be the (non-singular) population covariance of these samples. With respect to $\Sigma$, what is the most ...
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14 views

calculating distance among unordered set partitions for k-mean clustering?

I have a dataset for which I construct unordered set partitions for each data point, e.g. {{1,2,3}{4,6}{5}} for one and {{1,3}{2,4,5}{6}} for the next. I would like to perform k-means clustering on ...
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27 views

FAMES in case of Dynamic Time Warping

I found this paper Using Pivots to Speed-Up k-Medoids Clustering in which authors explain how to use triangular geometry and cosine law to speed up search of new medoids in case of K-medoids. My ...
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29 views

Appropriate distance measure between two finite state Markov chain models?

I am empirically creating Markov chains similar to this question. I end up with several finite state Markov chain models with the same nodes but varying transition probabilities. I want to calculate a ...
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21 views

Asymmetric distance measure in k-NN classifier?

What is the problem with an asymmetric distance measure in k-NN classifier? I think it will not cause problem, so long as I compute the distance consistently, say always from ...
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1answer
94 views

Get k most diverse objects from dendrogram (hierarchical clustering)

I have a dendrogram which groups similar object in a hierarchical order. The problem I try to solve is based on a dendrogram how to get k most diverse objects. E.g. We start with some random (?) ...
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30 views

Correlation of Distance Matrix

I have a matrix with 15 samples and ~10,000 data points (all z-scores). I calculated a distance matrix with euclidean distances using R. Is it valid to calculate and present a correlation on this ...
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30 views

Distance between independent observations of a categorical variable

I have a random variable $T: \{ \text{blue}, \text{green}, \text{red} \} \rightarrow [0,1]$ and a number of observations of $T$: ...
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13 views

Weights in computing mahalanobis distance

I need to compute distance among 200 observations and 17 variables. Variables are on different scales and not equally important. I computed Mahalanobis distance as Euclidean distance for the principal ...
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40 views

Can I compare Mahalanobis distances from different distributions?

I have a multivariate dataset representing multiple locations, each of which has a set of reference observations and a single test observation. For each location, I would like to measure how anomalous ...
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15 views

Online clustering with distances

I'm pretty new to this field so please excuse me if my question sounds naive. I have a stream of distance tuples in the form of (A, B, d) where ...
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94 views

Multivariate Outlier Detection with Robust Mahalanobis

I am searching some documents and examples related multivariate outlier detection with robust (minimum covariance estimation) mahalanobis distance. I have 6 variables and want to plot them to show ...
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28 views

Multivariate Mahalanobis Distance Vector Normalization

I have a vector including different variables with different scales. For instance ''a'' presents ''dollar value'' in billions.''b'' is a ratio, presents value divided by quantity and it ranges 0 to 1 ...
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2answers
145 views

Clustering based on large Jensen-Shannon Divergence distance matrix

I have a dataset with large number of features and about 15 000 observations. I’m using a probability distribution distance metric related to Jensen-Shannon divergence (JSD) to cluster the ...
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1answer
87 views

Distribution of the Levenshtein distance between two random strings

The Levenshtein or edit distance between two strings is the minimum number of edits (adding a letter, removing a letter or changing a letter) required to transform one into the other. Assume that we ...
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139 views

Definition of normalized Euclidean distance

Recently I have started looking for the definition of normalized Euclidean distance between two real vectors u and v. So far, I have discovered two apparently unrelated definitions: ...
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128 views

Comparing two vectors with the same numbers in different positions [closed]

I have two vectors of the same size representing one score for different sites (x and y coordinates) under distinct situations (each vector is one situation). At each vector the scores only change ...
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31 views

Testing whether neighbors are more similar to each other than distant points

Suppose you have points x1...xn in a metric space X, each is associated with some measurement y1...yn. I want to test whether points closer to each other in X have similar associated value y. I have ...
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56 views

Extending the Hellinger Distance of discrete probability distributions to multivariate distributions

For two discrete probability distributions P=(p1..pk) and Q=(q1...qk), their Hellinger distance is defined as $$H(P,Q)=\frac{1}{\sqrt{2}}\sqrt{\sum_{i=1}^k(\sqrt{p_i}-\sqrt{q_i})^2}$$ could this be ...
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47 views

pairwise distances used as features for classification

I have a feature matrix 977x3 features = rand(977,3); where each row is an observation and each column is a feature. I calculate the pairwise distances between ...
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124 views

Mahalanobis distance measure for clustering

Let's say I have a group of clusters. Would you recommend Mahalanobis distance measure for checking if new arrived data belongs to existing clusters or it is an outlier? Also, would you recommend ...
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107 views

How to measure consistency or simiarity between two data sets?

I am working on a study that elicits priorities (weights) from experts on a set of alternatives using different methods. The snapshot below shows the resulting weights, which sum up to 1 for each ...
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36 views

Kolmogorov-Smirnov and Hellinger distances

I am comparing two distributions with these two methods and sometimes I find no correlation between them! How is it possible? Which one is more believable? I use the D statistic from the KS test and ...
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48 views

t-test as Mahalanobis distance

Our tutor once said that the t-test applies Mahalanobis distance. Could you please explain how it does so?
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21 views

which distance for clustering

I've got 6000 reports that I've cleaned up. I've used 8 different steps to remove words of the reports. For each report, I've got a table of the following form: ...
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1answer
832 views

Gower distance with R functions; “gower.dist” and “daisy”

I have 9 numeric and 5 binary (0-1) variables, with 73 samples in my dataset. I know that the Gower distance is a good metric for datasets with mixed variables. I tried both daisy(cluster) and ...
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35 views

Test if paired data are more similar than non-paired data

I have a set of ten samples, comprised of five pairs of twins, and I have calculated the pairwise distances between all ten samples. The question I would like to answer with this data is: Are ...
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74 views

Probability that uniformly distributed points in a square region form a cluster

I have a known number of points N uniformly distributed in a square and I want to solve the expected number of clusters of points. I cluster is formed by a growing algorithm. Starting at a point p, ...
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86 views

Gower distance with R

I have 17 numeric and 5 binary (0-1) variables, with 73 samples in my dataset. I know that the Gower distance is a good metric for datasets with mixed variables. When I use daisy function in cluster ...
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41 views

Isolation by distance -data transformation

In population genetics a common analysis is to look for a correlation between genetic distance (e.g. FST) and geographic distance (km) using a scatterplot and linear regression. For this it seems a ...
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29 views

What is variance and co variance related to time series?

I'm trying to understand the Mahalanobis distance method which makes use of a covariance matrix. However i am not clear about the idea of variance and covariance with respect to time series. And also ...
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26 views

r-pnn, normalization and different distance measures for each variable

Since pnn is a NN that uses a Radial kernel to classify data, I think the distance measure is key and, in consequence, the normalization of the data. Am I right? How does pnn package calculate the ...
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239 views

Why are mixed data a problem for euclidean-based clustering algorithms?

Most classical clustering and dimensionality reduction algorithms (hierarchical clustering, principal component analysis, k-means, self-organizing maps...) are designed specifically for numeric data, ...
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1answer
302 views

How does the Gower distance calculate the difference between binary variables'?

I have 17 numeric and 5 binary (0-1) variables, with 73 samples in my dataset. I need to run a cluster analysis. I know that the Gower distance is a good metric for datasets with mixed variables. ...
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0answers
28 views

Unique matching for quantiles from one half of the density to a subset of the other half?

I am interested in finding the median absolute distance to quantiles. So, for $Q_\alpha$ the $0 \le \alpha \le 1$ quantile, I would like to find $Q_\gamma^*$ such that $Q_\gamma^*$ satisfies ...
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27 views

Want to findout satistical distance unsing another procedure except kullback liebler divergence

i want to find the distance between two pdf(pdf is calculated using kernel density estimator from two random data set of different size ) .Is there any alternative and efficent way to calculate ...
2
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1answer
68 views

Minimax space-filling design for 2 dimensions in practice

I think I understand the basic idea of a 2d minimax design. Given $n$ data points, choose locations for each point so that the maximum distance between anywhere in the input space and any of the $n$ ...
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130 views

Distance between two independent normal random variable

What is the PDF of $Z=\sqrt{(X-x_0)^2+(Y-y_0)^2}$ when X and y are i.i.d. zero mean normal random variable (i.e., $x\sim N(0,\sigma^2)$ and $x\sim N(0,\sigma^2)$)
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1answer
90 views

Euclidean distance with sparse and high dimension data

I have texts for a bunch of objects. From each text, I removed the stop words, and took each word as an attribute of the object. I then gave each word a rating based on sentiment analysis, so that the ...
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80 views

Average within-cluster distance using divisive clustering

I have to prove that the average within-cluster distance for 10 data points cannot increase when going from 1 cluster to 2 clusters (divisive clustering). Intuitively, it seems obvious that this is ...
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60 views

What is the relationship between naive Bayes and Mahalanobis distance

Recently, I found a code project which uses the Mahalanobis distance to compute Bayes value, but I don't know why you can do that. Second, as I know naive Bayes is based on the Bayes rule, and how ...