Drop collinear X columns in null model only if it has any (cholpred g…

…ives very large rank otherwise)
JuliaStats · Nov 29, 2022 · fa4b60e · fa4b60e
1 parent 48ffd9f
commit fa4b60e
Show file tree

Hide file tree

Showing 2 changed files with 7 additions and 2 deletions.
diff --git a/Project.toml b/Project.toml
@@ -17,7 +17,7 @@ StatsModels = "3eaba693-59b7-5ba5-a881-562e759f1c8d"
 [compat]
 DSP = "0.7"
 Distributions = "0.25"
-GLM = "1.5"
+GLM = "1.8"
 MLBase = "0.9"
 Reexport = "1"
 StatsBase = "0.33"

diff --git a/src/Lasso.jl b/src/Lasso.jl
@@ -330,8 +330,13 @@ function build_model(X::AbstractMatrix{T}, y::FPVector, d::UnivariateDistributio
  wts::Union{FPVector,Nothing}, offset::Vector, α::Real, nλ::Int,
  ω::Union{Vector, Nothing}, intercept::Bool, irls_tol::Real, dofit::Bool) where T
  # Fit to find null deviance
+ X0 = nullX(X, intercept, ω)
+
+ # Drop collinear X columns only if it has any (cholpred gives very large rank otherwise)
+ dropcollinear = size(X0,2) > 0
+
  # Maybe we should reuse this GlmResp object?
- nullmodel = fit(GeneralizedLinearModel, nullX(X, intercept, ω), y, d, l;
+ nullmodel = fit(GeneralizedLinearModel, X0, y, d, l; dropcollinear=dropcollinear,
  wts=wts, offset=offset, rtol=irls_tol, dofit=dofit)
  nulldev = deviance(nullmodel)
  nullb0 = intercept ? coef(nullmodel)[1] : zero(T)