Edit on GitHub

Changelog

[1.2.2]

Added

  • tests for Julia 1.9 in CI matrix
  • HDF5.jl v0.17 compatibility

[1.2.1]

Added

Fixed

  • error when constructing MCMCData with input distance matrix that has non-zero diagonal entries.
  • edge case for `fitprior2' when Kmin = Kmax = 1 or Kmin = Kmax = N generates a warning and fallback to default repulsion/cohesion parameters.

[1.2.0]

Added

  • added function fitprior2, alternative method to fit prior hyperparameters.

Changed

  • pretty print for MCMCResult also shows whether the model includes repulsion.
  • moved basic_example.jl from the examples folder to docs.
  • removed examples (added to a separate branch).

[1.1.0]

Added

  • added function signature for sampleK to accept individual parameters.

[1.0.1]

Documentation now updated to use Literate.jl to generate the example.

[1.0.0]

Added

  • examples from the main paper are now included in the examples folder. Data from the original paper is included in the data folder in the standard HDF5 format.
  • the examples now have more plots.
  • functionality to sample the distances from the prior predictive distribution (see sampledist).
  • functionality to sample $K$ from its marginal prior predictive (see sampleK).
  • generatemixture accepts a random number generator or a seed for the default RNG for reproducibility of results.

Removed

  • dependency on RCall and the various calls to the salso algorithm were removed. It is left to the user to make these calls if necessary.

[0.2.2]

Fixed

  • corrected time not printing in the correct format.
  • moved prettytime and prettynumber to utils.jl.

[0.2.1]

Added

  • added tests for pretty printing.
  • added tests for custom loss function in getpointestimate.

Fixed

  • verbose output in sampler missing newline.
  • custom loss function when computing a point estimate.

Removed

  • _infodist not in use, removed.

[0.2.0]

Added

  • added log-posterior to result.
  • added log-likelihood and log-posterior plots to basic example.
  • point-estimation via maximum likelihood and maximum a posteriori.
  • infodist function to compute the information distance between clusterings.
  • convenience constructor for MCMCData.
  • add verbose option for runsampler and fitprior.
  • pretty printing for MCMCData, MCMCOptionsList, and PriorHyperparamsList.
  • added bibliographic references to documentation.
  • added changelog.

Breaking

  • MCMCOptions constructor changed account for change in point-estimate calculation.
  • fitprior now only returns the hyperparameter list.
  • removed summarise for MCMCResult objects (use pretty printing instead).

Fixed

  • corrected computation of log-likelihood in result.
  • fixed edge case error in fitprior when the found value of K is either 1 or N. This case arises only for edge values of Kmin and Kmax, since the elbow method will otherwise not choose 1 or N for K.

Changed

  • added bounds checking for Kmin and Kmax in fitprior.
  • added input message for better debugging in fitprior.
  • added progress bar for fitprior if useR = false.
  • added input validation for generatemixture.
  • added input validation for binderloss and evaluateclustering.
  • added input validation for the constructors of MCMCData and MCMCOptionsList.
  • separated computation of log-likelihood and log-prior.
  • removed redundant loss function calculations when computing point-estimate.
  • Binder loss calculation (binderloss) is now approximate (using randindex from Clustering.jl) but faster.
  • runsampler no longer automatically calculates a point estimate.
  • summarise has a separate signature for MCMC output and for point estimate summary, and now provides more measures for point estimates.
  • minor optimisations using @inbounds, @simd, and @turbo.
  • using StaticArrays.jl and separate function for restricted Gibbs scan.
  • speedup via non-generic implementation of matrix and vector sums with LoopVectorization.jl.