JACKKNIFE Jackknife statistics.
    JACKSTAT = JACKKNIFE(JACKFUN,...) draws jackknife data samples,
    computes statistics on each sample using the function JACKFUN, and
    returns the results in the matrix JACKSTAT.  JACKFUN is a function 
    handle specified with @. Each row of JACKSTAT contains the results of
    applying JACKFUN to one jackknife sample.  If JACKFUN returns a matrix
    or array, then this output is converted to a row vector for storage in
    JACKSTAT.
 
    The third and later input arguments to JACKKNIFE are data (scalars,
    column vectors, or matrices) that are used to create inputs to JACKFUN.
    JACKKNIFE creates each jackknife sample by sampling with replacement
    from the rows of the non-scalar data arguments (these must have the
    same number of rows).  Scalar data are passed to JACKFUN unchanged.
 
    Examples:
 
    Estimate the bias of the MLE variance estimator of random samples
    taken from the vector Y using jackknife.  The bias has a known formula
    in this problem, so we can compare the jackknife value to this formula.
 
       y = exprnd(5,100,1);
       m = jackknife(@var, y, 1);
       n = length(y);
       bias = var(y,1) - var(y,0)         % known bias formula
       jbias = (n - 1)*(mean(m)-var(y,1)) % jackknife estimate of the bias
 
    See also bootstrp, random, randsample, hist, ksdensity.

    Reference page in Help browser
       doc jackknife