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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.
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```@docs
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predict
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```
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The `predict` function has two main methods:
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1. For `AbstractVector{<:AbstractVarInfo}` - useful when you have a collection of `VarInfo` objects representing posterior samples.
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2. For `MCMCChains.Chains` - useful when you have posterior samples in the form of a `Chains` object from MCMCChains.jl.
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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.
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