dapper
1.1.0Data Augmentation for Private Posterior Estimation
Overview
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.
Install
Health
- OK2026-08-0513 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- NOTE2026-08-0112 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 97%
- Return-value docs
- 100%
- References docs
- 50%
Downloads
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Dependencies
Code & Tests
People & History
3 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 1.1.0Latest
- RR 4.5.0 released · 2025-04-11
- 1.0.12024-10-29 · diff ↗
- 1.0.02024-07-09
- RR 4.4.0 released · 2024-04-24
Package metadata
- First published
- 2024-07-09
- Total releases
- 3 / 2 yrs
- License
- MIT + file LICENSE OSI
- Download size
- 11 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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