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

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https://www.banglajol.info/index.php/ijss/article/view/70112

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https://doi.org/10.3329/ijss.v23i2.70112
 http://hdl.handle.net/11603/31715

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UMBC Mathematics and Statistics Department
UMBC Faculty Collection
UMBC Student Collection

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Author/Creator ORCID

https://orcid.org/0000-0001-6361-8295

Date

2023-11-30

Type of Work

journal articles
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Citation of Original Publication

Guin, Abhishek, Anindya Roy, and Bimal Sinha. “Bayesian Analysis of Singly Imputed Synthetic Data under the Multivariate Normal Model.” International Journal of Statistical Sciences 23, no. 2 (November 30, 2023): 1–18. https://doi.org/10.3329/ijss.v23i2.70112.

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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