Tagged Questions

0
votes
3answers
350 views

Automatic outlier detection in R

Our model processes millions of multivariate observations; manual outlier detection is impractical. I am looking for a method of automatic outlier detection. I have been trying to use R package ...
1
vote
0answers
84 views

Hypothesis testing to determine cluster outliers

I have a cluster of $p$-dimensional data from $n$ samples which is assumed to be normally distributed as a multivariate Gaussian with sample mean ${\bar{\mu}}$ and sample covariance matrix ...
3
votes
1answer
363 views

Mahalanobis distance distribution of multivariate normally distributed points

I'm trying to understand the properties of Mahalanobis distance of multivariate random points (my final goal is to use Mahalanobis distance for outlier detection). My calculations are in python. I ...
1
vote
3answers
251 views

Identifying outlier data in high-dimensional settings

I have a data set with high-dimensional feature space. Are there any pre-processing methodologies that can detect outliers from this data set? The outlier, I mean, are the ones that tend to be very ...
11
votes
2answers
621 views

Distribution of an observation-level Mahalanobis distance

If I have a multivariate normal i.i.d. sample $X_1, \ldots, X_n \sim N_p(\mu,\Sigma)$, and define $$d_i^2(b,A) = (X_i - b)' A^{-1} (X_i - b)$$ (which is sort of a Mahalanobis distance [squared] from a ...
0
votes
2answers
177 views

Fitting a curve to the edge of a distribution

I need to be able to find outliers in my data. I thought it best to test for this using the Kolmogorov-Smirnov Test. I have over 800,000 points so I wanted a way to filter the data first to only ...