Matrix: LPnetlib/lp_fit1d

Description: Netlib LP problem fit1d: minimize c'*x, where Ax=b, lo<=x<=hi

LPnetlib/lp_fit1d graph
(bipartite graph drawing)


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  • Matrix group: LPnetlib
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  • download as a MATLAB mat-file, file size: 28 KB. Use UFget(624) or UFget('LPnetlib/lp_fit1d') in MATLAB.
  • download in Matrix Market format, file size: 41 KB.
  • download in Rutherford/Boeing format, file size: 29 KB.

    Matrix properties
    number of rows24
    number of columns1,049
    structural full rank?yes
    structural rank24
    # of blocks from dmperm1
    # strongly connected comp.1
    explicit zero entries0
    nonzero pattern symmetry 0%
    numeric value symmetry 0%
    Cholesky candidate?no
    positive definite?no

    authorR. Fourer
    editorR. Fourer
    kindlinear programming problem
    2D/3D problem?no

    Additional fieldssize and type
    bfull 24-by-1
    cfull 1049-by-1
    lofull 1049-by-1
    hifull 1049-by-1
    z0full 1-by-1


    A Netlib LP problem, in lp/data.  For more information                    
    send email to with the message:                           
    	 send index from lp                                                      
    	 send readme from lp/data                                                
    The following are relevant excerpts from lp/data/readme (by David M. Gay):
    The column and nonzero counts in the PROBLEM SUMMARY TABLE below exclude  
    slack and surplus columns and the right-hand side vector, but include     
    the cost row.  We have omitted other free rows and all but the first      
    right-hand side vector, as noted below.  The byte count is for the        
    MPS compressed file; it includes a newline character at the end of each   
    line.  These files start with a blank initial line intended to prevent    
    mail programs from discarding any of the data.  The BR column indicates   
    whether a problem has bounds or ranges:  B stands for "has bounds", R     
    for "has ranges".  The BOUND-TYPE TABLE below shows the bound types       
    present in those problems that have bounds.                               
    The optimal value is from MINOS version 5.3 (of Sept. 1988)               
    running on a VAX with default options.                                    
                           PROBLEM SUMMARY TABLE                              
    Name       Rows   Cols   Nonzeros    Bytes  BR      Optimal Value         
    FIT1D        25   1026    14430      51734  B    -9.1463780924E+03        
            BOUND-TYPE TABLE                                                  
    FIT1D      UP                                                             
    Supplied by Bob Fourer.                                                   
    When included in Netlib: Cost coefficients negated.                       
    Concerning FIT1D, FIT1P, FIT2D, FIT2P, Bob Fourer says                    
        The pairs FIT1P/FIT1D and FIT2P/FIT2D are primal and                  
        dual versions of the same two problems [except that we                
        have negated the cost coefficients of the dual problems               
        so all are minimization problems].  They originate from               
        a model for fitting linear inequalities to data, by                   
        minimization of a sum of piecewise-linear penalties.                  
        The FIT1 problems are based on 627 data points and 2-3                
        pieces per primal pl penalty term.  The FIT2 problems                 
        are based on 3000 data points (from a different sample                
        altogether) and 4-5 pieces per pl term.                               
    Added to Netlib on  31 Jan. 1990                                          

    Ordering statistics:result
    nnz(V) for QR, upper bound nnz(L) for LU, with COLAMD24,624
    nnz(R) for QR, upper bound nnz(U) for LU, with COLAMD300

    SVD-based statistics:
    null space dimension0
    full numerical rank?yes

    singular values (MAT file):click here
    SVD method used:s = svd (full (R)) ; where [~,R,E] = spqr (A') with droptol of zero

    LPnetlib/lp_fit1d 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.