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dapper  

Data Augmentation for Private Posterior Estimation
View on CRAN: Click here


Download and install dapper package within the R console
Install from CRAN:
install.packages("dapper")

Install from Github:
library("remotes")
install_github("cran/dapper")

Install by package version:
library("remotes")
install_version("dapper", "1.1.1")



Attach the package and use:
library("dapper")
Maintained by
Kevin Eng
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-07-09
Latest Update: 2024-10-29
Description:
A data augmentation based sampler for conducting privacy-aware Bayesian inference. The dapper_sample() function takes an existing sampler as input and automatically constructs a privacy-aware sampler. The process of constructing a sampler is simplified through the specification of four independent modules, allowing for easy comparison between different privacy mechanisms by only swapping out the relevant modules. Probability mass functions for the discrete Gaussian and discrete Laplacian are provided to facilitate analyses dealing with privatized count data. The output of dapper_sample() can be analyzed using many of the same tools from the 'rstan' ecosystem. For methodological details on the sampler see Ju et al. (2022) <doi:10.48550/arXiv.2206.00710>, and for details on the discrete Gaussian and discrete Laplacian distributions see Canonne et al. (2020) <doi:10.48550/arXiv.2004.00010>.
How to cite:
Kevin Eng (2024). dapper: Data Augmentation for Private Posterior Estimation. R package version 1.1.1, https://cran.r-project.org/web/packages/dapper. Accessed 03 Oct. 2026.
Previous versions and publish date:
(2026-09-06 15:00), 1.0.0 (2024-07-09 18:10), 1.0.1 (2024-10-29 06:10), 1.1.0 (2026-02-02 07:31)
Other packages that cited dapper R package
View dapper citation profile
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Complete documentation for dapper
Functions, R codes and Examples using the dapper R package
Full dapper package functions and examples
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