Processing math: 0%

mahalCorAna

mahalCorAna computes Mahalanobis distances (in squared units) for each row of matrix Y

Syntax

Description

example

d =mahalCorAna(Y, MU) Example of computation of MD.

Examples

expand all

  • Example of computation of MD.
  • Generate a contingency table.

    nrow=30;
    ncol=5;
    % Fix the marginals of the two rows
    nrowt=200*ones(1,nrow);
    % Fix the marginals of the three columns
    ncolt=1200*ones(ncol,1);
    % Generate the contingency table
    out=rcontFS(nrow,ncol,nrowt,ncolt);
    N=out.m144;
    MU=sum(N,1)/sum(nrowt);
    % Compute MD ;
    n=sum(N,'all');
    P=N/n;
    ProfileRows=P./sum(P,1);
    d=mahalCorAna(ProfileRows,MU);

    Related Examples

    expand all

  • Find total inertial of contingency table Generate a contingency table.
  • nrow=30;
    ncol=5;
    % Fix the marginals of the two rows
    nrowt=200*ones(1,nrow);
    % Fix the marginals of the three columns
    ncolt=1200*ones(ncol,1);
    % Generate the contingency table
    out=rcontFS(nrow,ncol,nrowt,ncolt);
    N=out.m144;
    n=sum(N,'all');
    P=N/n;
    r=sum(P,2); % row masses
    c=sum(P,1); % centroid of row masses
    ProfileRows=P./r;
    d2=r.*mahalCorAna(ProfileRows,c);
    % d2 is the total inertia
    disp('Total inertia')
    disp(sum(d2));

    Input Arguments

    expand all

    Y — Input data. Matrix.

    I x J Profile rows matrix; n observations and v variables.

    Rows of Y represent observations, and columns represent variables.

    Data Types: single|double

    MU — Centroid. Vector.

    1 x J vector containing centroid and covariance matrix to use

    Data Types: single| double

    Output Arguments

    expand all

    d —Mahalanobis distances. Vector

    n x 1 vector which contains the squared Mahalanobid distances.

    References

    See Also

    This page has been automatically generated by our routine publishFS


    The developers of the toolbox The forward search group Terms of Use Acknowledgments