Optimal design subsampling from Big Datasets

Laura Deldossi, Chiara Tommasi

Risultato della ricerca: Contributo in rivistaArticolo in rivista


Big Data are huge amounts of digital information that rarely result from properly planned surveys; as a consequence they often contain redundant observations. When the aim is to answer particular questions of interest, we suggest selecting a subsample of units that contains the majority of the information to achieve this goal. Selection methods driven by the theory of optimal design incorporate the inferential purposes and thus perform better than standard sampling schemes.
Lingua originaleEnglish
pagine (da-a)93-101
Numero di pagine9
RivistaJournal of Quality Technology
Stato di pubblicazionePubblicato - 2022


  • design efficiency
  • finite population sampling
  • optimal design theory


Entra nei temi di ricerca di 'Optimal design subsampling from Big Datasets'. Insieme formano una fingerprint unica.

Cita questo