Changes in version 0.4.2 (2017-07-18)                  

  - Second vignette bernstein on: Bernstein approximations and use of
    DPMechBernstein for private function release.
  - Minor edits to docs

                        Changes in version 0.4.1                        

  - Expanding test coverage of Bernstein mechanism and function
    approximation code.

                        Changes in version 0.4.0                        

  - Addition of S3 constructor and predict() generic implementation for
    fitting (non-iterated) Bernstein polynomial function approximations.
  - Addition of DPMechBernstein class implementing the Bernstein
    mechanism of Alda and Rubinstein (AAAI'2017), for privately
    releasing functions.
  - Bug fix in the Laplace random sampler affecting DPMechLaplace
  - Unit test coverage of new functionality; general documentation
    improvements.

                        Changes in version 0.3.2                        

  - Addition of DPMechGaussian class for the generic Gaussian mechanism
    to README, Vignette. Resolves #2
  - Minor test additions.

                        Changes in version 0.3.1                        

  - Refactoring around releaseResponse() method in DPMechNumeric.
    Resolves #1
  - Increased test coverage.

                        Changes in version 0.3.0                        

  - New DPMechGaussian class implementing the Gaussian mechanism, which
    achieves (epsilon,delta)-differential privacy by adding Gaussian
    noise to numeric responses calibrated by L2-norm sensitivity.
  - Refactoring of DPMechGaussian and DPMechLaplace underneath a new
    VIRTUAL class DPMechNumeric which contains common methods, dims slot
    (formerly dim changed because dim is a special slot for S4).

                        Changes in version 0.2.0                        

  - DPMechLaplace objects can now be initialized without specifying
    non-private target response dim. In such cases, the sensitivity
    sampler will perform an additional target probe to determine dim.

                      Changes in version 0.1.0.901                      

  - Sensitivity sampler methods no longer require oracles that return
    lists. Acceptable oracles may now return lists, matrices, data
    frames, numeric vectors, or char vectors. As a consequence some
    example code in docs, README and vignette, is simplified.

                      Changes in version 0.1.0.900                      

  - Initial release