[jira] [Updated] (SPARK-8884) 1-sample Anderson-Darling Goodness-of-Fit test

["Feynman Liang (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-8884?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Feynman Liang updated SPARK-8884:
---------------------------------
    Target Version/s: 1.5.0

> 1-sample Anderson-Darling Goodness-of-Fit test
> ----------------------------------------------
>
>                 Key: SPARK-8884
>                 URL: https://issues.apache.org/jira/browse/SPARK-8884
>             Project: Spark
>          Issue Type: New Feature
>          Components: MLlib
>            Reporter: Jose Cambronero
>            Priority: Minor
>
> We have implemented a 1-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 for all except normal/exponential (in which case they are estimated from the data). 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.



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org