Modularize constructors (#449)

* split constructor into steps

* don't forget the weights

* news update

NEWS.md

@@ -1,3 +1,7 @@
+MixedModels v3.1.4 Release Notes
+========================
+* [experimental] Additional convenience constructors for `LinearMixedModel` [#449]
+
 MixedModels v3.1.3 Release Notes
 ========================
 * Compatibility updates
@@ -120,3 +124,4 @@ Package dependencies
 [#444]: https://github.com/JuliaStats/MixedModels.jl/issues/444
 [#446]: https://github.com/JuliaStats/MixedModels.jl/issues/446
 [#447]: https://github.com/JuliaStats/MixedModels.jl/issues/447
+[#449]: https://github.com/JuliaStats/MixedModels.jl/issues/449

Project.toml

@@ -1,7 +1,7 @@
 name = "MixedModels"
 uuid = "ff71e718-51f3-5ec2-a782-8ffcbfa3c316"
 author = ["Phillip Alday <[email protected]>", "Douglas Bates <[email protected]>", "Jose Bayoan Santiago Calderon <[email protected]>"]
-version = "3.1.3"
+version = "3.1.4"
 
 [deps]
 Arrow = "69666777-d1a9-59fb-9406-91d4454c9d45"

src/linearmixedmodel.jl

@@ -69,6 +69,25 @@ function LinearMixedModel(
 
     y, Xs = modelcols(form, tbl)
 
+    return LinearMixedModel(y, Xs, form, wts)
+end
+
+"""
+    LinearMixedModel(y, Xs, form)
+
+Private constructor for a LinearMixedModel.
+
+To construct a model, you only need the response (`y`), already assembled
+model matrices (`Xs`), schematized formula (`form`) and weights (`wts`).
+Everything else in the structure can be derived from these quantities.
+
+!!! note
+    This method is internal and experimental and so may change or disappear in
+    a future release without being considered a breaking change.
+"""
+function LinearMixedModel(y::AbstractArray,
+                           Xs::Tuple, # can't be more specific here without stressing the compiler
+                           form::FormulaTerm, wts = [])
     y = reshape(float(y), (:, 1)) # y as a floating-point matrix
     T = promote_type(Float64, eltype(y))  # ensure that eltype of model matrices is at least Float64
     y = convert(Matrix{T}, y)
@@ -97,6 +116,26 @@ function LinearMixedModel(
     end
     push!(feterms, FeMat(y, [""]))
 
+    return LinearMixedModel(feterms, reterms, form, wts)
+end
+
+"""
+    LinearMixedModel(feterms, reterms, form, wts=[])
+
+Private constructor for a `LinearMixedModel` given already assembled fixed and random effects.
+
+To construct a model, you only need a vector of `FeMat`s (the fixed-effects
+model matrix and response), a vector of `AbstractReMat` (the random-effects
+model matrices), the formula and the weights. Everything else in the structure
+can be derived from these quantities.
+
+!!! note
+    This method is internal and experimental and so may change or disappear in
+    a future release without being considered a breaking change.
+"""
+function LinearMixedModel(feterms::Vector{FeMat{T}}, reterms::Vector{AbstractReMat{T}},
+                          form::FormulaTerm, wts=[]) where T
+
     # detect and combine RE terms with the same grouping var
     if length(reterms) > 1
         reterms = amalgamate(reterms)