Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A method to find an efficient and robust sampling strategy under model
  uncertainty   We consider the problem of deciding on sampling strategy, in particular
sampling design. We propose a risk measure, whose minimizing value guides the
choice. The method makes use of a superpopulation model and takes into account
uncertainty about its parameters. The method is illustrated with a real
dataset, yielding satisfactory results. As a baseline, we use the strategy that
couples probability proportional-to-size sampling with the difference
estimator, as it is known to be optimal when the superpopulation model is fully
known. We show that, even under moderate misspecifications of the model, this
strategy is not robust and can be outperformed by some alternatives

17
The categories of this paper are: q-fin
10
The categories of this paper are: q-bio
13
The categories of this paper are: quant-ph
35
The categories of this paper are: mtrl-th
22
The categories of this paper are: chao-dyn
20
The categories of this paper are: acc-phys
4
The categories of this paper are: cond-mat
21
The categories of this paper are: adap-org
26
The categories of this paper are: bayes-an
27
The categories of this paper are: comp-gas
1
The categories of this paper are: cs
9
The categories of this paper are: nlin
8
The categories of this paper are: hep-ex
6
The categories of this paper are: astro-ph
36
The categories of this paper are: cmp-lg
23
The categories of this paper are: solv-int