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Co-authored-by: Tor Erlend Fjelde <[email protected]>

src/AbstractMCMC.jl

@@ -81,18 +81,12 @@ The `MCMCSerial` algorithm allows users to sample serially, with no thread or pr
 struct MCMCSerial <: AbstractMCMCEnsemble end
 
 """
-    getparams(model::AbstractModel, state)
-    getparams(logdensity, state)
-    getparams(state)
+    getparams([model::AbstractModel, ]state)
 
 Retrieve the values of parameters from the sampler's `state` as a `Vector{<:Real}`.
 """
 function getparams end
 
-function getparams(logdensity, state)
-    return getparams(_model(logdensity), state)
-end
-
 function getparams(model::AbstractModel, state)
     return getparams(state)
 end
@@ -111,17 +105,11 @@ Although not enforced, it should hold that `setparams!!(state, getparams(state))
 words, the sampler should implement a consistent transformation between its internal representation
 and the vector representation of the parameter values.
 
-Sometimes, to maintain the consistency of the log density and parameter values, a `model::AbstractModel`
+Sometimes, to maintain the consistency of the log density and parameter values, a `model`
 should be provided. This is useful for samplers that need to evaluate the log density at the new parameter values.
-If `model` is not an `AbstractMCMC.AbstractModel`, by default, it is assumed to be a log density function following 
-the `LogDensityProblems.jl` interface, and will be wrapped with [`AbstractMCMC.LogDensityModel`](@ref).
 """
 function setparams!! end
 
-function setparams!!(logdensity, state, params)
-    return setparams!!(_model(logdensity), state, params)
-end
-
 function setparams!!(model::AbstractModel, state, params)
     return setparams!!(state, params)
 end