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We could in principle support estimating the ESS for quite a few more estimators:
var
percentile
Base.Fix1{mean}
geomean
harmmean
genmean
skewness
kurtosis
Base.Fix2{moment}
mad
All but the first 3 require identifying suitable expectand proxies and overloading _expectand_proxy accordingly. In every case, the proxy needs to be rigorously tested with a simulation study on distributions with various shapes. I worked on this some time ago for several of these, so this is mostly a note for self to finish that work and add the results here.
We can similarly overload mcse using the same proxy, where we generally need to do some extra work to estimate the variance of the estimator. This would in general be faster than our mcse fallback and probably be less likely to underestimate the MCSE.
The text was updated successfully, but these errors were encountered:
We could in principle support estimating the ESS for quite a few more estimators:
var
percentile
Base.Fix1{mean}
geomean
harmmean
genmean
skewness
kurtosis
Base.Fix2{moment}
mad
All but the first 3 require identifying suitable expectand proxies and overloading
_expectand_proxy
accordingly. In every case, the proxy needs to be rigorously tested with a simulation study on distributions with various shapes. I worked on this some time ago for several of these, so this is mostly a note for self to finish that work and add the results here.We can similarly overload
mcse
using the same proxy, where we generally need to do some extra work to estimate the variance of the estimator. This would in general be faster than ourmcse
fallback and probably be less likely to underestimate the MCSE.The text was updated successfully, but these errors were encountered: