• SJSU Singular Matrix Database
  • Matrix group: Pajek
  • Click here for a description of the Pajek group.
  • Click here for a list of all matrices
  • Click here for a list of all matrix groups

  • Matrix: Pajek/EVA
  • Description: Pajek network: EVA, corporate inter-relationships
  • download as a MATLAB mat-file, file size: 238 KB. Use SJget(284) or SJget('Pajek/EVA') in MATLAB.
  • download in Matrix Market format, file size: 79 KB.
  • download in Rutherford/Boeing format, file size: 81 KB.


    Routine svd from Matlab (R2008a) used to calculate the singular values.


    scc of Pajek/EVA

    Matrix properties (click for a legend)  
    number of rows8,497
    number of columns8,497
    structural full rank?no
    structural rank1,303
    numerical rank 1,301
    dimension of the numerical null space7,196
    numerical rank / min(size(A))0.15311
    Euclidean norm of A 23.495
    calculated singular value # 13010.47103
    numerical rank defined using a tolerance
    max(size(A))*eps(norm(A)) =
    calculated singular value # 13022.2036e-013
    gap in the singular values at the numerical rank:
    singular value # 1301 / singular value # 1302
    calculated condition numberInf
    # of blocks from dmperm766
    # strongly connected comp.8,482
    explicit zero entries0
    nonzero pattern symmetry 0%
    numeric value symmetry 0%
    Cholesky candidate?no
    positive definite?no

    authorK. Norlen, G. Lucas, M. Gebbie, J. Chuang
    editorV. Batagelj
    kinddirected graph
    2D/3D problem?no

    Additional fieldssize and type
    nodenamefull 8497-by-85


    Pajek network converted to sparse adjacency matrix for inclusion in UF sparse 
    matrix collection, Tim Davis.  For Pajek datasets, See V. Batagelj & A. Mrvar,

    Ordering statistics:AMD METIS
    nnz(chol(P*(A+A'+s*I)*P'))15,529 16,372
    Cholesky flop count3.2e+004 5.1e+004
    nnz(L+U), no partial pivoting22,561 24,247
    nnz(V) for QR, upper bound nnz(L) for LU8,593 8,576
    nnz(R) for QR, upper bound nnz(U) for LU348,642 347,869

    Maintained by Leslie Foster, last updated 24-Apr-2009.

    Entries 5 through 14 in the table of matrix properties and the singular
    value plot were created using SJsingular code. The other plots
    and statistics are produced using utilities from the SuiteSparse package.
    Matrix color plot pictures by cspy, a MATLAB function in the CSparse package.