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Assessing Statistical Disclosure Risk for Differentially Private, Hierarchical Count Data, with Application to the 2020 US Decennial Census

Publication ,  Preprint
Kazan, Z; Reiter, J
Published in: Statistica Sinica
October 1, 2024
Published version (DOI) Link to item

Duke Scholars

Zeki Kazan
Author Zeki Kazan  
Jerome P. Reiter
Author Jerome P. Reiter Statistical Science

Published In

Statistica Sinica

DOI

10.5705/ss.202022.0187

Publication Date

October 1, 2024

Publisher

Academia Sinica, Institute of Statistical Science

Related Subject Headings

  • Statistics & Probability
  • 4905 Statistics
  • 0801 Artificial Intelligence and Image Processing
  • 0199 Other Mathematical Sciences
  • 0104 Statistics
 

Citation

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Kazan, Zeki, and Jerry Reiter. “Assessing Statistical Disclosure Risk for Differentially Private, Hierarchical Count Data, with Application to the 2020 US Decennial Census.” Statistica Sinica, October 1, 2024. https://doi.org/10.5705/ss.202022.0187.
Kazan, Zeki, and Jerry Reiter. “Assessing Statistical Disclosure Risk for Differentially Private, Hierarchical Count Data, with Application to the 2020 US Decennial Census.” Statistica Sinica, Academia Sinica, Institute of Statistical Science, Oct. 2024. Manual, doi:10.5705/ss.202022.0187.
Kazan Z, Reiter J. Assessing Statistical Disclosure Risk for Differentially Private, Hierarchical Count Data, with Application to the 2020 US Decennial Census. Statistica Sinica. Academia Sinica, Institute of Statistical Science; 2024 Oct 1;

Published In

Statistica Sinica

DOI

10.5705/ss.202022.0187

Publication Date

October 1, 2024

Publisher

Academia Sinica, Institute of Statistical Science

Related Subject Headings

  • Statistics & Probability
  • 4905 Statistics
  • 0801 Artificial Intelligence and Image Processing
  • 0199 Other Mathematical Sciences
  • 0104 Statistics