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