A simulated annealing-based algorithm for selecting balanced samples
A simulated annealing-based algorithm for selecting balanced samples
Balanced sampling is a random method for sample selection, the use of which is preferable when auxiliary information is available for all units of a population. However, implementing balanced sampling can be a challenging task, and this is due in part to the computational efforts required and the necessity to respect balancing constraints and inclusion probabilities. In the present paper, a new algorithm for selecting balanced samples is proposed. This method is inspired by simulated annealing algorithms, as a balanced sample selection can be interpreted as an optimization problem. A set of simulation experiments and an example using real data shows the efficiency and the accuracy of the proposed algorithm.
Auxiliary variables, Balanced sampling, Sampling algorithms, Simulated annealing
491-505
Benedetti, Roberto
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Dickson, Maria Michela
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Espa, Giuseppe
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Pantalone, Francesco
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Piersimoni, Federica
38b51a17-1b20-4c0f-b18a-5cae8e255d57
1 March 2022
Benedetti, Roberto
1197c065-613f-4074-b103-4cbd5dd9bec8
Dickson, Maria Michela
500b8a6d-fe5d-4d4f-935f-e5f90298a500
Espa, Giuseppe
5693184f-8d14-4e25-9b8d-78936fff4224
Pantalone, Francesco
c1b85bef-a71c-4851-9807-7776bc0b5ded
Piersimoni, Federica
38b51a17-1b20-4c0f-b18a-5cae8e255d57
Benedetti, Roberto, Dickson, Maria Michela, Espa, Giuseppe, Pantalone, Francesco and Piersimoni, Federica
(2022)
A simulated annealing-based algorithm for selecting balanced samples.
Computational Statistics, 37 (1), .
(doi:10.1007/s00180-021-01113-3).
Abstract
Balanced sampling is a random method for sample selection, the use of which is preferable when auxiliary information is available for all units of a population. However, implementing balanced sampling can be a challenging task, and this is due in part to the computational efforts required and the necessity to respect balancing constraints and inclusion probabilities. In the present paper, a new algorithm for selecting balanced samples is proposed. This method is inspired by simulated annealing algorithms, as a balanced sample selection can be interpreted as an optimization problem. A set of simulation experiments and an example using real data shows the efficiency and the accuracy of the proposed algorithm.
Text
s00180-021-01113-3
- Version of Record
More information
Accepted/In Press date: 5 May 2021
e-pub ahead of print date: 26 May 2021
Published date: 1 March 2022
Additional Information:
Funding Information:
Open access funding provided by Università degli Studi di Trento within the CRUI-CARE Agreement.
Publisher Copyright:
© 2021, The Author(s).
Keywords:
Auxiliary variables, Balanced sampling, Sampling algorithms, Simulated annealing
Identifiers
Local EPrints ID: 475302
URI: http://eprints.soton.ac.uk/id/eprint/475302
ISSN: 0943-4062
PURE UUID: 22101857-080f-4c49-b5c9-2419db1a9c4c
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Date deposited: 15 Mar 2023 17:31
Last modified: 17 Mar 2024 04:10
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Contributors
Author:
Roberto Benedetti
Author:
Maria Michela Dickson
Author:
Giuseppe Espa
Author:
Francesco Pantalone
Author:
Federica Piersimoni
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