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Published June 27, 2017 | Version v0.10.0
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dmbates/MixedModels.jl: Fix loglikelihood calculation with weights

Creators

  • 1. University of Wisconsin
  • 2. Princeton Neuroscience Institute
  • 3. Ined (National Institute for Demographic Studies)
  • 4. University of Washington
  • 5. UNC Epidemiology

Description

  • Fixes #89
  • Adds more benchmarks
  • Introduces and uses model_response(mf::ModelFrame, d::Distribution) to convert a binary PooledDataArray response to a 0/1 floating point vector. This should be done in DataFrames and a pull request will be made for this.
  • pass the random number generator to the simulate! method
  • methods for A_rdiv_Bc!, etc. that are now in Base are commented with if VERSION < ...
  • allow a contrasts specification in lmm and glmm

Files

dmbates/MixedModels.jl-v0.10.0.zip

Files (7.8 MB)

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md5:0909d8f5f189e877937f4c6a771d9262
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Additional details

Related works

Is supplement to
https://github.com/dmbates/MixedModels.jl/tree/v0.10.0 (URL)