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2 changes: 1 addition & 1 deletion docs/make.jl
Original file line number Diff line number Diff line change
Expand Up @@ -22,7 +22,7 @@ makedocs(;
# The API index.html page is fairly large, and violates the default HTML page size
# threshold of 200KiB, so we double that.
format=Documenter.HTML(; size_threshold=2^10 * 400),
modules=[DynamicPPL],
modules=[DynamicPPL, Base.get_extension(DynamicPPL, :DynamicPPLMCMCChainsExt)],
pages=[
"Home" => "index.md", "API" => "api.md", "Internals" => ["internals/varinfo.md"]
],
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10 changes: 5 additions & 5 deletions docs/src/api.md
Original file line number Diff line number Diff line change
Expand Up @@ -108,14 +108,14 @@ unfix

DynamicPPL provides functionality for generating samples from the posterior predictive distribution through the `predict` function. This allows you to use posterior parameter samples to generate predictions for unobserved data points.

```@docs
predict
```

The `predict` function has two main methods:

1. For `AbstractVector{<:AbstractVarInfo}` - useful when you have a collection of `VarInfo` objects representing posterior samples.
2. For `MCMCChains.Chains` - useful when you have posterior samples in the form of a `Chains` object from MCMCChains.jl.
2. For `MCMCChains.Chains` (only available when `MCMCChains.jl` is loaded) - useful when you have posterior samples in the form of an `MCMCChains.Chains` object.

```@docs
predict
```

### Basic Usage

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