[ANN] Metida.jl: mixed-effects models fitting package

Community Package announcements
, ,
#1

Metida.jl is a Julia package for fitting mixed-effects models with flexible covariance structure.

Implemented covariance structures:

  • Scaled Identity (SI)
  • Diagonal (DIAG)
  • Autoregressive (AR)
  • Heterogeneous Autoregressive (ARH)
  • Compound Symmetry (CS)
  • Heterogeneous Compound Symmetry (CSH)
  • Autoregressive Moving Average (ARMA)

All structures can be applied to the random (G) or repeated ® part of the variance-covariance matrix (V). Where:

V = ZGZ' + R

Documentation available here.

v0.2.3

  • Documentation
  • FullDummyCoding fix
  • FunctionTerm fix
15 Likes
#2

Version 0.3.0 released.

Now random/repeated model syntax is near classic R/MixedModel style:

    lmm = LMM(@formula(var~sequence+period+formulation), df0;
    random = VarEffect(@covstr(formulation|subject), CSH),
    repeated = VarEffect(@covstr(formulation|subject), DIAG),
    )
    fit!(lmm)

No more subject keyword: now blocking factor construct automatically. Other minor things and documentation…

3 Likes
#3

Version 0.4.0 released.

New covariance types:

  • Toeplitz
  • ToeplitzParameterized
  • CustomCovarianceType

I think CustomCovarianceType is a really interesting thing. Users can specify methods to construct covariance matrix, G and R parts separately. Read more in docs…

1 Like
#4

Version 0.6.0 released.

New covariance types:

  • HeterogeneousToeplitz
  • HeterogeneousToeplitzParameterized

Some changes in API, rho-link function, validation & documentation.

#5

Hello.

How does it compare to the MixedEffects.jl package in terms of memory usage, speed and capabilities?

1 Like
#6

Hello! MixedModels.jl much faster, and consume less memory. If Mixed Models.jl applicable for your task it will be better to use MixedModels.jl If you need Satterthwaite ddf approximation, analysis with repeated measurements, or application of some nontrivial covariance structures - Metida.jl solve these problems. I didn’t found MixedEffects.jl maybe you mean MixedModels.jl, anyway if I missed this package, please guide me to it.

1 Like