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From "Cody Warren (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (MATH-1423) SingularMatrixException on Non-Square Matrix
Date Thu, 29 Jun 2017 20:23:00 GMT

    [ https://issues.apache.org/jira/browse/MATH-1423?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16068929#comment-16068929
] 

Cody Warren commented on MATH-1423:
-----------------------------------

Hi Phil,

Sorry I actually meant 60 attributes and 2160 observations.  Where is the user group???  Some
more documentation on some of that would be nice as well though.  



> SingularMatrixException on Non-Square Matrix
> --------------------------------------------
>
>                 Key: MATH-1423
>                 URL: https://issues.apache.org/jira/browse/MATH-1423
>             Project: Commons Math
>          Issue Type: Bug
>    Affects Versions: 3.5
>         Environment: Oracle JDK 1.8.121
>            Reporter: Cody Warren
>            Priority: Minor
>              Labels: OLSMutlipleRegression, SingularMatrixException
>   Original Estimate: 1h
>  Remaining Estimate: 1h
>
> I'm trying to implement an OLSMultipleLinearRegression class in the apache commons math
java library and I keep getting a "SingularMatrixException". This is confusing to me because
my data isn't even square (60 x 2160) which I thought was a requirement for a Singular Matrix.
> I've played with the data by pruning rows off and adding them back on, and found differing
numbers of rows that will work/fail with this dataset.
> Also, I've checked my matrix for columns or rows that are full of zeros as suggested
in this post:
> Using Apache Library for OLS Regression : Matrix is singular exception
> Is there something else with this library that I don't understand? Is there a way I can
make this more robust or predict a singular array beforehand?



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