Jackknife estimate of the standard deviation of a parameter estimate.
s=stdjack(x,T) [s,y]=stdjack(x,T)
a matrix of doubles
a function or a list, the function which computes the empirical estimate from x.
a 1-by-1 matrix of doubles, the estimate of the standard deviation
a 1-by-n matrix of doubles, the values of T of the resamples, where n is the size of the parameter estimate
Jackknife estimate of the standard deviation of the parameter estimate T(x).
The function T must have the following header:
p=T(x)
x
is the sample or the resample
and p
is a m-by-1 matrix of doubles.
In the case where the parameter estimate has a more general
shape (e.g. 2-by-2), the shape of p
is reshaped
into a column vector with m
components.
See "T and extra arguments" for details on how to pass extra-arguments to T.
The function is equal to
sqrt(diag(covjack(x,T)))
n = 20; x=distfun_chi2rnd(3,n,1); m=mean(x) // Empirical mean s=stdev(x)/sqrt(n) // Standard error for the mean s=stdjack(x,mean) // Standard error with Jackknife // Get y [s,y]=stdjack(x,mean); size(y) // Estimate the standard deviation of the median m=median(x) s=stdjack(x,median) // With extra arguments x=distfun_chi2rnd(3,50,5); mean(x,"r") [s,y]=stdjack(x,list(mean,"r")); size(y) | ![]() | ![]() |