Variance estimation by Permutation Samples

(a Project)


It was nice that someone could check the following strategy I´ll try to put in action:

Algorithm:
To obtain a generic variance estimate*, var, then its Confidence Interval by:

First step: to find MM by the permutation X´, (MM denoting the modified mean)
__MM = [j*x´j]/c__
__ c = n*(1+n)/2
Second step: to get a new data Permutation X´´ and
_ssd = [(x´´j - MM)^2]
Third step
_var = ssd/(n-1)

* repeated a larger number of times to be possible a CI estimation, which I suppose (I hope) narrower than the conventional algorithm:
___ [xj - xbar]^2 /(n-1).
___xbar = [xj] / n

_licas (Luís A. Afonso)
.

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