Bayesian Analysis of Singly Imputed Synthetic Data under the Multivariate Normal Model

Authors

  • Abhishek Guin University of Maryland, Baltimore County, Maryland, USA
  • Anindya Roy University of Maryland, Baltimore County, Maryland, USA
  • Bimal Sinha University of Maryland, Baltimore County, Maryland, USA

DOI:

https://doi.org/10.3329/ijss.v23i2.70112

Keywords:

Bayesian credible sets, Multivariate normal, Plug-in sampling, Posterior predictive sampling, Synthetic data.

Abstract

We develop appropriate Bayesian procedures to draw inference about the parameters under a multivariate normal model based on synthetic data. We consider two standard forms of synthetic data, generated under plug in sampling method and posterior predictive sampling method. In addition to point estimates of the mean vector and dispersion matrix, Bayesian credible sets for the mean vector and the generalized variance are also provided under both the scenarios. The analysis in the case when some (partial) features are sensitive and need to be hidden is also briey indicated.

Vol. 23(2), November, 2023, pp 1-18

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Published

2023-11-30

How to Cite

Guin, A. ., Roy, . A., & Sinha, . B. . (2023). Bayesian Analysis of Singly Imputed Synthetic Data under the Multivariate Normal Model. International Journal of Statistical Sciences, 23(2), 1–18. https://doi.org/10.3329/ijss.v23i2.70112

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Section

Original Articles