add mvnormalcanon

JuliaStats · May 31, 2022 · e416cb6 · e416cb6
1 parent 7883de3
commit e416cb6
Showing 1 changed file with 17 additions and 17 deletions.
diff --git a/src/multivariate/mvnormalcanon.jl b/src/multivariate/mvnormalcanon.jl
@@ -19,7 +19,7 @@ which is also a subtype of `AbstractMvNormal` to represent a multivariate normal
 canonical parameters. Particularly, `MvNormalCanon` is defined as:
 
 ```julia
-struct MvNormalCanon{T<:Real,P<:AbstractPDMat,V<:AbstractVector} <: AbstractMvNormal
+struct MvNormalCanon{T<:Real,P,V<:AbstractVector} <: AbstractMvNormal
     μ::V    # the mean vector
     h::V    # potential vector, i.e. inv(Σ) * μ
     J::P    # precision matrix, i.e. inv(Σ)
@@ -40,10 +40,19 @@ const ZeroMeanIsoNormalCanon{Axes}  = MvNormalCanon{Float64, ScalMat{Float64},
 
 **Note:** `MvNormalCanon` share the same set of methods as `MvNormal`.
 """
-struct MvNormalCanon{T<:Real,P<:AbstractPDMat,V<:AbstractVector} <: AbstractMvNormal
+struct MvNormalCanon{T<:Real,P,V<:AbstractVector} <: AbstractMvNormal
     μ::V    # the mean vector
     h::V    # potential vector, i.e. inv(Σ) * μ
     J::P    # precision matrix, i.e. inv(Σ)
+
+    function MvNormalCanon{T,P,V}(μ::V, h::AbstractVector, J::P) where {T<:Real, V<:AbstractVector{T}, P}
+        length(μ) == length(h) == dim(J) || throw(DimensionMismatch("Inconsistent argument dimensions"))
+        if typeof(μ) === typeof(h)
+            return new{T,typeof(J),typeof(μ)}(μ, h, J)
+        else
+            return new{T,typeof(J),Vector{T}}(collect(μ), collect(h), J)
+        end
+    end
 end
 
 const FullNormalCanon = MvNormalCanon{Float64,PDMat{Float64,Matrix{Float64}},Vector{Float64}}
@@ -56,26 +65,17 @@ const ZeroMeanIsoNormalCanon{Axes}  = MvNormalCanon{Float64,ScalMat{Float64},Zer
 
 
 ### Constructors
-function MvNormalCanon(μ::AbstractVector{T}, h::AbstractVector{T}, J::AbstractPDMat{T}) where {T<:Real}
-    length(μ) == length(h) == dim(J) || throw(DimensionMismatch("Inconsistent argument dimensions"))
-    if typeof(μ) === typeof(h)
-        return MvNormalCanon{T,typeof(J),typeof(μ)}(μ, h, J)
-    else
-        return MvNormalCanon{T,typeof(J),Vector{T}}(collect(μ), collect(h), J)
-    end
-end
-
-function MvNormalCanon(μ::AbstractVector{T}, h::AbstractVector{T}, J::AbstractPDMat) where {T<:Real}
+function MvNormalCanon(μ::AbstractVector{T}, h::AbstractVector{T}, J::P) where {T<:Real, P}
     R = promote_type(T, eltype(J))
-    MvNormalCanon(convert(AbstractArray{R}, μ), convert(AbstractArray{R}, h), convert(AbstractArray{R}, J))
+    MvNormalCanon{T,P,typeof(μ)}(convert(AbstractArray{R}, μ), convert(AbstractArray{R}, h), convert(AbstractArray{R}, J))
 end
 
-function MvNormalCanon(μ::AbstractVector{<:Real}, h::AbstractVector{<:Real}, J::AbstractPDMat)
+function MvNormalCanon(μ::AbstractVector{<:Real}, h::AbstractVector{<:Real}, J)
     R = Base.promote_eltype(μ, h, J)
     MvNormalCanon(convert(AbstractArray{R}, μ), convert(AbstractArray{R}, h), convert(AbstractArray{R}, J))
 end
 
-function MvNormalCanon(h::AbstractVector{<:Real}, J::AbstractPDMat)
+function MvNormalCanon(h::AbstractVector{<:Real}, J)
     length(h) == dim(J) || throw(DimensionMismatch("Inconsistent argument dimensions"))
     R = Base.promote_eltype(h, J)
     hh = convert(AbstractArray{R}, h)
@@ -89,7 +89,7 @@ end
 Construct a multivariate normal distribution with potential vector `h` and precision matrix
 `J`.
 """
-MvNormalCanon(h::AbstractVector{<:Real}, J::AbstractMatrix{<:Real}) = MvNormalCanon(h, PDMat(J))
+MvNormalCanon(h::AbstractVector{<:Real}, J::Matrix{<:Real}) = MvNormalCanon(h, PDMat(J))
 MvNormalCanon(h::AbstractVector{<:Real}, J::Diagonal{<:Real}) = MvNormalCanon(h, PDiagMat(J.diag))
 MvNormalCanon(μ::AbstractVector{<:Real}, J::Union{Symmetric{<:Real,<:Diagonal{<:Real}},Hermitian{<:Real,<:Diagonal{<:Real}}}) = MvNormalCanon(μ, PDiagMat(J.data.diag))
 function MvNormalCanon(h::AbstractVector{<:Real}, J::UniformScaling{<:Real})
@@ -170,7 +170,7 @@ sqmahal!(r::AbstractVector, d::MvNormalCanon, x::AbstractMatrix) = quad!(r, d.J,
 
 # Sampling (for GenericMvNormal)
 
-unwhiten_winv!(J::AbstractPDMat, x::AbstractVecOrMat) = unwhiten!(inv(J), x)
+unwhiten_winv!(J::AbstractMatrix, x::AbstractVecOrMat) = unwhiten!(inv(J), x)
 unwhiten_winv!(J::PDiagMat, x::AbstractVecOrMat) = whiten!(J, x)
 unwhiten_winv!(J::ScalMat, x::AbstractVecOrMat) = whiten!(J, x)
 if isdefined(PDMats, :PDSparseMat)