GitHub user hhbyyh opened a pull request:
https://github.com/apache/spark/pull/11780
[SPARK-8884][MLlib] 1-sample Anderson-Darling Goodness-of-Fit test
## What changes were proposed in this pull request?
This is a continued work of @josepablocam in
https://github.com/apache/spark/pull/7278. As sync in jira,
https://issues.apache.org/jira/browse/SPARK-8884, I'll help with the rest work.
I've resolve the conflict and made some small changes.
I plan to add more ut for other distribution yet met some problem and hope
to discuss it here.
We have implemented one-sample Anderson-Darling goodness-of-fit test to add
to the current hypothesis testing functionality. The current implementation
supports various distributions (normal, exponential, gumbel, logistic, and
weibull). However, users must provide distribution parameters. In contrast to
other tests, such as the Kolmogorov Smirnov test, we only support specific
distributions as the critical values depend on the distribution being tested.
The distributed implementation of AD takes advantage of the fact that we
can calculate a portion of the statistic within each partition of a sorted data
set, independent of the global order of those observations. We can then carry
some additional information that allows us to adjust the final amounts once we
have collected 1 result per partition.
## How was this patch tested?
unit tests and some manual comparison with R and Python.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/hhbyyh/spark adtest
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/11780.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #11780
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commit a9a59cba0d0ba29c8a483a6bf18426db14d59860
Author: Yuhao Yang <[email protected]>
Date: 2016-03-16T10:34:45Z
ad test
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