Missing docstring for loglikelihood

[cgarling]

On the latest version of the documentation, the following docstring is missing as there is no method with this signature defined. It looks like this should be loglikelihood(::UnivariateDistribution, ::Real) instead.

Distributions.jl/docs/src/univariate.md

Line 76 in a9b0e3c

loglikelihood(::UnivariateDistribution, ::AbstractArray)

[mschauer]

The vectorised version left us with d6985ad#diff-c185a88dade2ce18f68ff0130b5626734ed3cdb341bf5765dbb008fd8a6d91a0

loglikelihood(::UnivariateDistribution, ::Real) should have a docstring though, did it get lost there?

[cgarling]

I am unfortunately not a git wizard but it looks to me like the relevant method definition is

Distributions.jl/src/univariates.jl

Lines 329 to 330 in f33af97

	# loglikelihood for `Real`
	Base.@propagate_inbounds loglikelihood(d::UnivariateDistribution, x::Real) = logpdf(d, x)

for which I do not see a docstring.

[cgarling]

P.S. It looks like pdf(::MultivariateDistribution, ::AbstractArray) and logpdf(::MultivariateDistribution, ::AbstractArray) are also included in the documentation but do not exist. I don't use the multivariate models much so I'm not sure what changed, but if I had to guess maybe these are the correct methods now?

Distributions.jl/src/common.jl

Lines 198 to 234 in f33af97

	"""
	pdf(d::Distribution{ArrayLikeVariate{N}}, x::AbstractArray{<:Real,N}) where {N}
	Evaluate the probability density function of `d` at `x`.
	This function checks if the size of `x` is compatible with distribution `d`. This check can
	be disabled by using `@inbounds`.
	# Implementation
	Instead of `pdf` one should implement `_pdf(d, x)` which does not have to check the size of
	`x`. However, since the default definition of `pdf(d, x)` falls back to `logpdf(d, x)`
	usually it is sufficient to implement `logpdf`.
	See also: [`logpdf`](@ref).
	"""
	@inline function pdf(
	d::Distribution{ArrayLikeVariate{N}}, x::AbstractArray{<:Real,M}
	) where {N,M}
	if M == N
	@boundscheck begin
	size(x) == size(d) ||
	throw(DimensionMismatch("inconsistent array dimensions"))
	end
	return _pdf(d, x)
	else
	@boundscheck begin
	M > N ||
	throw(DimensionMismatch(
	"number of dimensions of the variates ($M) must be greater than or equal to the dimension of the distribution ($N)"
	))
	ntuple(i -> size(x, i), Val(N)) == size(d) ||
	throw(DimensionMismatch("inconsistent array dimensions"))
	end
	return @inbounds map(Base.Fix1(pdf, d), eachvariate(x, variate_form(typeof(d))))
	end
	end

Distributions.jl/src/common.jl

Lines 240 to 275 in f33af97

	"""
	logpdf(d::Distribution{ArrayLikeVariate{N}}, x::AbstractArray{<:Real,N}) where {N}
	Evaluate the logarithm of the probability density function of `d` at `x`.
	This function checks if the size of `x` is compatible with distribution `d`. This check can
	be disabled by using `@inbounds`.
	# Implementation
	Instead of `logpdf` one should implement `_logpdf(d, x)` which does not have to check the
	size of `x`.
	See also: [`pdf`](@ref).
	"""
	@inline function logpdf(
	d::Distribution{ArrayLikeVariate{N}}, x::AbstractArray{<:Real,M}
	) where {N,M}
	if M == N
	@boundscheck begin
	size(x) == size(d) ||
	throw(DimensionMismatch("inconsistent array dimensions"))
	end
	return _logpdf(d, x)
	else
	@boundscheck begin
	M > N ||
	throw(DimensionMismatch(
	"number of dimensions of the variates ($M) must be greater than or equal to the dimension of the distribution ($N)"
	))
	ntuple(i -> size(x, i), Val(N)) == size(d) ||
	throw(DimensionMismatch("inconsistent array dimensions"))
	end
	return @inbounds map(Base.Fix1(logpdf, d), eachvariate(x, variate_form(typeof(d))))
	end
	end