Tagged Questions

1
vote
2answers
149 views

Is this outlier merely unusual or does it signify manipulation?

These are actual reported costs (60) for a series of projects for two years, say USD (though actually not) totalling $57,975,403.24: ...
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 ...
0
votes
0answers
31 views

Anomaly prediction confidence for frequentist vs bayesian parameter inference

I am comparing the behavior of some implementations of Bayesian and frequentist approaches to parametric anomaly detection and currently trying to figure out the differences when the sample set is ...
0
votes
3answers
78 views

How to use LOF for outlier detection as I have training and test dataset?

I want to use the Local Outlier Factor (LOF) algorithm for outlier detection but it simply finds outliers on unlabed data as whole and you do not need to have a training and test set. However in my ...
0
votes
1answer
109 views

Estimate density from neighbor distances

Assuming I have a data set of known size, and there is one object that I want to test for being in an approximately uniform distributed region of the data set. For the query object, I know the $k$ ...
4
votes
2answers
199 views

How to judge if a datapoint deviates substantially from the norm

This is statistics 101, but I'm not a statistician and so can't seem to find the right technical jargon to google. My company collects data at discreet points through time. Today's datapoint is ...
3
votes
2answers
137 views

Detecting fishy data

Just a little thought I've been having. If we rolled a fair dice 60 times, and got 60 sixes in a row, we would (wrongly?) definitely assume that something fishy's going on. Is there any statistical ...
1
vote
1answer
126 views

Statistical test for finding significant positions having deviated values

I have near about 50 files(each file corresponds to a patient) with 4 columns - chromosome start.position stop.pos value First 3 columns in all 50 files are same and fourth column is ...
0
votes
0answers
127 views

Identifying outliers

I have binomial frequency data for an allele associated with populations living in mountainous. These mountains run north to south where sites are nearly fixed for this allele and lowland sites to the ...
6
votes
3answers
306 views

Dealing with “trouble maker” samples

I have a pretty large data set (~300 cases with ~40 continuous attributes, binary labeled) which I used to create several alternative predictive models. To do this, the set was divided to training and ...
6
votes
1answer
2k views

On univariate outlier tests (or: Dixon Q versus Grubbs)

In (most of) the analytical chemistry literature, the standard test for detecting outliers in univariate data (e.g. a sequence of measurements of some parameter) is Dixon's Q test. Invariably, all the ...