DPpack

Description

An implementation of common statistical analysis and models with differential privacy (Dwork et al., 2006a) <doi:10.1007/11681878_14> guarantees. The package contains, for example, functions providing differentially private computations of mean, variance, median, histograms, and contingency tables. It also implements some statistical models and machine learning algorithms such as linear regression (Kifer et al., 2012) <https://proceedings.mlr.press/v23/kifer12.html> and SVM (Chaudhuri et al., 2011) <https://jmlr.org/papers/v12/chaudhuri11a.html>. In addition, it implements some popular randomization mechanisms, including the Laplace mechanism (Dwork et al., 2006a) <doi:10.1007/11681878_14>, Gaussian mechanism (Dwork et al., 2006b) <doi:10.1007/11761679_29>, analytic Gaussian mechanism (Balle & Wang, 2018) <https://proceedings.mlr.press/v80/balle18a.html>, and exponential mechanism (McSherry & Talwar, 2007) <doi:10.1109/FOCS.2007.66>.

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Namespaces in Imports field not imported from:
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Namespaces in Imports field not imported from:
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Namespaces in Imports field not imported from:
  ‘R6’ ‘dplyr’ ‘ggplot2’ ‘nloptr’
  All declared Imports should be used.

Namespaces in Imports field not imported from:
  ‘R6’ ‘dplyr’ ‘ggplot2’ ‘nloptr’
  All declared Imports should be used.

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