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@TomMonks TomMonks released this 06 Feb 14:47
· 53 commits to master since this release
v0.3.0
bfd7afe
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GPG key ID: B5690EEEBB952194
Learn about vigilant mode.

Changes:

  • Distributions classes now have python type hints.
  • Added distributions and time dependent arrivals via thinning example notebooks.
  • Added datasets module and function to load example NSPP dataset.
  • Distributions added
    • Erlang (mean and stdev parameters)
    • ErlangK (k and theta parameters)
    • Poisson
    • Beta
    • Gamma
    • Weibull
    • PearsonV
    • PearsonVI
    • Discrete (values and observed frequency parameters)
    • ContinuousEmpirical (linear interpolation between groups)
    • RawEmpirical (resample with replacement from individual X's)
    • TruncatedDistribution (arbitrary truncation of any distribution)
  • Added sim_tools.time_dependent module that contains NSPPThinning class for modelling time dependent arrival processes.
  • Updated test suite for distributions and thinning
  • Basic Jupyterbook of documentation.
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