43 citations · 84 across the 4 of their papers we have counts for
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Convolved subsampling estimation with applications to block bootstrap
Johannes Tewes, Daniel J. Nordman, Dimitris N. Politis
The block bootstrap approximates sampling distributions from dependent data by resampling data blocks. A fundamental problem is establishing its consistency for the distribution of…
A frequency domain empirical likelihood method for irregularly spaced spatial data
Soutir Bandyopadhyay, Soumendra N. Lahiri, Daniel J. Nordman
This paper develops empirical likelihood methodology for irregularly spaced spatial data in the frequency domain. Unlike the frequency domain empirical likelihood (FDEL) methodolog…
A note on the stationary bootstrap's variance
Daniel J. Nordman
Because the stationary bootstrap resamples data blocks of random length, this method has been thought to have the largest asymptotic variance among block bootstraps Lahiri [Ann. St…
On optimal spatial subsample size for variance estimation
Daniel J. Nordman, Soumendra N. Lahiri
We consider the problem of determining the optimal block (or subsample) size for a spatial subsampling method for spatial processes observed on regular grids. We derive expansions…