Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

backport of QR to 1.x #537

Open
wants to merge 9 commits into
base: v1
Choose a base branch
from
Open

backport of QR to 1.x #537

Show file tree
Hide file tree
Changes from 1 commit
Commits
Show all changes
9 commits
Select commit Hold shift + click to select a range
cd7b2b1
`QR` decomposition method in GLM.
mousum-github May 4, 2023
2d91725
Link(::TableRegressionModel)
palday Jun 7, 2023
97cab57
oh contravariance
palday Jun 7, 2023
ae88551
oh TableRegressionModel
palday Jun 7, 2023
173d3b7
predict got more complicated
palday Jun 7, 2023
5269e7a
test updates
palday Jun 7, 2023
23321a8
version bump
palday Jun 7, 2023
92ec3fa
doctest fixes
palday Jun 7, 2023
cd187fb
Apply suggestions from code review
palday Jun 7, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 2 additions & 0 deletions src/glmfit.jl
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -643,6 +643,8 @@ function dispersion(m::AbstractGLM, sqr::Bool=false)
end
end

dispersion(m::StatsModels.TableRegressionModel{<:AbstractGLM}, args...; kwargs...) = dispersion(m.model, args...; kwargs...)

"""
predict(mm::AbstractGLM, newX::AbstractMatrix; offset::FPVector=eltype(newX)[],
interval::Union{Symbol,Nothing}=nothing, level::Real = 0.95,
Expand Down
1 change: 1 addition & 0 deletions src/linpred.jl
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -386,6 +386,7 @@ coef(obj::LinPredModel) = coef(obj.pp)
dof_residual(obj::LinPredModel) = nobs(obj) - dof(obj) + 1

hasintercept(m::LinPredModel) = any(i -> all(==(1), view(m.pp.X , :, i)), 1:size(m.pp.X, 2))
hasintercept(m::StatsModels.TableRegressionModel{<:LinPredModel}) = hasintercept(m.mf.f)

linpred_rank(x::LinPred) = length(x.beta0)
linpred_rank(x::DensePredChol{<:Any, <:CholeskyPivoted}) = rank(x.chol)
Expand Down
6 changes: 5 additions & 1 deletion src/negbinfit.jl
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -38,6 +38,9 @@ function mle_for_θ(y::AbstractVector, μ::AbstractVector, wts::AbstractVector;
θ
end

_rr(m::StatsModels.TableRegressionModel{<:GeneralizedLinearModel}) = m.model.rr
_rr(m::GeneralizedLinearModel) = m.rr

"""
negbin(formula, data, [link::Link];
<keyword arguments>)
Expand Down Expand Up @@ -139,7 +142,8 @@ function negbin(F,
regmodel = glm(F, D, NegativeBinomial(θ), args...;
dropcollinear=dropcollinear, method=method, maxiter=maxiter,
atol=atol, rtol=rtol, verbose=verbose, kwargs...)
μ = regmodel.rr.mu

μ = _rr(regmodel).mu
Copy link
Member

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Above the code seems to assume that regmodel is a TableRegressionModel, so you could just do regmodel.model.rr.mu and remove _rr.

prevθ = θ
θ = mle_for_θ(y, μ, wts; maxiter=maxiter, tol=rtol)
δ = prevθ - θ
Expand Down