Matrix: Pajek/Erdos991

Description: Pajek network: Erdos collaboration network

Pajek/Erdos991 graph
(undirected graph drawing)


Pajek/Erdos991
scc of Pajek/Erdos991

  • Home page of the UF Sparse Matrix Collection
  • 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
  • download as a MATLAB mat-file, file size: 12 KB. Use UFget(1469) or UFget('Pajek/Erdos991') in MATLAB.
  • download in Matrix Market format, file size: 9 KB.
  • download in Rutherford/Boeing format, file size: 8 KB.

    Matrix properties
    number of rows492
    number of columns492
    nonzeros2,834
    # strongly connected comp.43
    explicit zero entries0
    nonzero pattern symmetrysymmetric
    numeric value symmetrysymmetric
    typebinary
    structuresymmetric
    Cholesky candidate?no
    positive definite?no

    authorJ. Grossman, P. Iain, R. Castro
    editorV. Batagelj
    date2006
    kindundirected graph
    2D/3D problem?no

    Additional fieldssize and type
    nodenamefull 492-by-33

    Notes:

    ------------------------------------------------------------------------------
    Pajek network converted to sparse adjacency matrix for inclusion in UF sparse 
    matrix collection, Tim Davis.  For Pajek datasets, See V. Batagelj & A. Mrvar,
    http://vlado.fmf.uni-lj.si/pub/networks/data/.                                
    ------------------------------------------------------------------------------
    

    SVD-based statistics:
    norm(A)17.1252
    min(svd(A))0
    cond(A)Inf
    rank(A)435
    null space dimension57
    full numerical rank?no
    singular value gap1.08716e+12

    singular values (MAT file):click here
    SVD method used:s = svd (full (A)) ;
    status:ok

    Pajek/Erdos991 svd

    For a description of the statistics displayed above, click here.

    Maintained by Tim Davis, last updated 12-Mar-2014.
    Matrix pictures by cspy, a MATLAB function in the CSparse package.
    Matrix graphs by Yifan Hu, AT&T Labs Visualization Group.