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.

A simulated annealing-based algorithm for selecting balanced samples / Benedetti, R.; Dickson, M. M.; Espa, G.; Pantalone, F.; Piersimoni, F.. - In: COMPUTATIONAL STATISTICS. - ISSN 0943-4062. - 2021:(2021). [10.1007/s00180-021-01113-3]

A simulated annealing-based algorithm for selecting balanced samples

Dickson M. M.;Espa G.;
2021-01-01

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.
2021
Benedetti, R.; Dickson, M. M.; Espa, G.; Pantalone, F.; Piersimoni, F.
A simulated annealing-based algorithm for selecting balanced samples / Benedetti, R.; Dickson, M. M.; Espa, G.; Pantalone, F.; Piersimoni, F.. - In: COMPUTATIONAL STATISTICS. - ISSN 0943-4062. - 2021:(2021). [10.1007/s00180-021-01113-3]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/328716
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