MixedModels.jl
MixedModels.jl copied to clipboard
A Julia package for fitting (statistical) mixed-effects models
- Although this commit allows for `rankUpdate!` of the upper triangle it turns out that this is much slower than updating the lower triangle. ```julia julia> using BenchmarkTools, LinearAlgebra, MixedModels...
- This is the first stage exploration of returning tabular representations for some of the `MixedModel` properties through `TypedTables.jl` - Change the result of `raneftables` to be a `NamedTuple` of...
Currently there is an inconsistency in both the argument name and its default between `fit!`, which has a `progress` argument defaulting to `true`, and `parametricbootstrap` which has a `hide_progress` argument...
xref: https://github.com/JuliaStats/StatsModels.jl/pull/261
At present the allpars property of a parametric bootstrap sample is usually converted immediately to a DataFrame for manipulation. We probably don't want to have MixedModels.jl depend on DataFrames.jl but...
I wanted to `predict` a few values, but it said ```jl julia> MixedModels.predict(fitval, d) ERROR: ArgumentError: only one level found: 2016 (need at least two to compute contrasts). ``` My...
In the `Construction` section of the package documentation, it is said ```In contrast, the `cask` grouping factor is *nested* within the `batch` grouping factor in the *Pastes* data.``` I know...
If we want to have fitlog contain the initial and final parameter and objective values and have the `.initial`, `.final` fields just point to those values we should expand the...
This happens e.g. when users have number of successes instead of proportion of successes.
One potential downside to this approach is that it does make it possible to get stuck and/or have the optimizer believe that the initial values are the optimum. The former...