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Force return type on pwrss and logdet to provide stable type inference on objective #771

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Jun 20, 2024
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Force return type on pwrss and logdet to provide stable type inference on objective #771

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4 changes: 2 additions & 2 deletions src/linalg/logdet.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -25,11 +25,11 @@ lower Cholesky factor.
"""
function LinearAlgebra.logdet(m::LinearMixedModel{T}) where {T}
L = m.L
@inbounds s = sum(j -> LD(L[kp1choose2(j)]), axes(m.reterms, 1))
@inbounds s = sum(j -> LD(L[kp1choose2(j)]), axes(m.reterms, 1))::T
if m.optsum.REML
lastL = last(L)
s += LD(lastL) # this includes the log of sqrtpwrss
s -= log(last(lastL)) # so we need to subtract it from the sum
end
return s + s # multiply by 2 b/c the desired det is of the symmetric mat, not the factor
return (s + s)::T # multiply by 2 b/c the desired det is of the symmetric mat, not the factor
end
10 changes: 5 additions & 5 deletions src/linearmixedmodel.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -50,7 +50,7 @@ function LinearMixedModel(
end

const _MISSING_RE_ERROR = ArgumentError(
"Formula contains no random effects; this isn't a mixed model. Perhaps you want to use GLM.jl?",
"Formula contains no random effects; this isn't a mixed model. Perhaps you want to use GLM.jl?"
)

function LinearMixedModel(
Expand All @@ -62,7 +62,7 @@ function LinearMixedModel(
fvars ⊆ tvars ||
throw(
ArgumentError(
"The following formula variables are not present in the table: $(setdiff(fvars, tvars))",
"The following formula variables are not present in the table: $(setdiff(fvars, tvars))"
),
)

Expand Down Expand Up @@ -226,7 +226,7 @@ end
function _offseterr()
return throw(
ArgumentError(
"Offsets are not supported in linear models. You can simply shift the response by the offset.",
"Offsets are not supported in linear models. You can simply shift the response by the offset."
),
)
end
Expand Down Expand Up @@ -372,7 +372,7 @@ function StatsBase.confint(m::MixedModel{T}; level=0.95) where {T}
return DictTable(;
coef=coefnames(m),
lower=β .- cutoff .* std,
upper=β .+ cutoff .* std
upper=β .+ cutoff .* std,
)
end

Expand Down Expand Up @@ -895,7 +895,7 @@ end

The penalized, weighted residual sum-of-squares.
"""
pwrss(m::LinearMixedModel) = abs2(last(last(m.L)))
pwrss(m::LinearMixedModel{T}) where {T} = abs2(last(last(m.L)))::T

"""
ranef!(v::Vector{Matrix{T}}, m::MixedModel{T}, β, uscale::Bool) where {T}
Expand Down
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