fix docs

Author: penelopeysm

docs/src/api.md

@@ -154,22 +154,6 @@ When using `predict` with `MCMCChains.Chains`, you can control which variables a
   - `include_all=false` (default): Include only newly predicted variables
   - `include_all=true`: Include both parameters from the original chain and predicted variables
 
-## Marginalisation
-
-DynamicPPL provides the `marginalize` function to marginalise out variables from a model.
-This requires `MarginalLogDensities.jl` to be loaded in your environment.
-
-```@docs
-marginalize
-```
-
-A `MarginalLogDensity` object acts as a function which maps non-marginalised parameter values to a marginal log-probability.
-To retrieve a VarInfo object from it, you can use:
-
-```@docs
-VarInfo(::MarginalLogDensities.MarginalLogDensity{<:DPPLMLDExt.LogDensityFunctionWrapper}, ::Union{AbstractVector,Nothing})
-```
-
 ## Models within models
 
 One can include models and call another model inside the model function with `left ~ to_submodel(model)`.