[jira] [Updated] (MATH-1403) Collinearity test: QR Decomposition rank incorrect (SVD ok)

["Rob Tompkins (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/MATH-1403?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Rob Tompkins updated MATH-1403:
-------------------------------
    Fix Version/s: 4.0

> Collinearity test: QR Decomposition rank incorrect (SVD ok)
> -----------------------------------------------------------
>
>                 Key: MATH-1403
>                 URL: https://issues.apache.org/jira/browse/MATH-1403
>             Project: Commons Math
>          Issue Type: Bug
>    Affects Versions: 3.6.1
>         Environment: Linux ubuntu
> JDK 8
>            Reporter: Hugo Ferrira
>             Fix For: 4.0
>
>
> Hello,
> I am aware that such a question have been asked before but I cannot seem to solve this issue for a very simple example. The closest example I have is:
> https://issues.apache.org/jira/browse/MATH-1100
> from which I could not get an answer.
> I am trying to copy an algorithm from R's Caret package that identifies collinear columns of a matrix [1]. I am assuming a "long" matrix and and am using the trivial example from the reference above. However I cannot get this to work because the QR's rank result is incorrect.
> I have the following example:
> import org.apache.commons.math3.linear.RealMatrix;
> import org.apache.commons.math3.linear.RRQRDecomposition;
> import org.apache.commons.math3.linear.Array2DRowRealMatrix;
> import org.apache.commons.math3.linear.SingularValueDecomposition ;
> public class QRIssue {
>   public static void main(String[] args) {
>     double[][] am = new double[5][];
>     double[] c1 = new double[] {1.0, 1.0, 1.0, 1.0, 1.0, 1.0} ;
>     double[] c2 = new double[] {1.0, 1.0, 1.0, 0.0, 0.0, 0.0} ;
>     double[] c3 = new double[] {0.0, 0.0, 0.0, 1.0, 1.0, 1.0} ;
>     double[] c4 = new double[] {1.0, 0.0, 0.0, 1.0, 0.0, 0.0 } ;
>     double[] c6 = new double[] {0.0, 0.0, 1.0, 0.0, 0.0, 1.0 } ;
>     am[0] = c1 ;
>     am[1] = c2 ;
>     am[2] = c3 ;
>     am[3] = c4 ;
>     am[4] = c6 ;
>     Double threshold = 1e-1;
>     Array2DRowRealMatrix m = new Array2DRowRealMatrix( am, false )  ; // use array, don't copy
>     RRQRDecomposition qr = new RRQRDecomposition( m,  threshold) ;
>     RealMatrix r = qr.getR() ;
>     int numColumns = r.getColumnDimension() ;
>     int rank = qr.getRank( threshold ) ;
>     System.out.println("QR rank: " + rank) ;
>     System.out.println("QR is singular: " + !qr.getSolver().isNonSingular()) ;
>     System.out.println("QR is singular: " + (numColumns == rank) ) ;
>     SingularValueDecomposition sv2 = new org.apache.commons.math3.linear.SingularValueDecomposition(m);
>     System.out.println("SVD rank: " + sv2.getRank()) ;
>     }
> }
> For SVD I get a rank of 4 which is correct (columns 0,1,2 are collinear : c0 = c1 + c2). But for QR I get 5. I have tried several thresholds with no success. For several subsets of the columns above (example only 0,1,2 I get the correct answer). What am I doing wrong?
> TIA,
> Hugo F.
> 1. https://topepo.github.io/caret/pre-processing.html#lindep



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