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Update README.md and reexport MCMCSerial #66

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Oct 20, 2021
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Update README.md and reexport MCMCSerial #66

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Update README.md
devmotion Oct 20, 2021
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Reexport MCMCSerial
devmotion Oct 20, 2021
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devmotion Oct 20, 2021
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Update README.md
devmotion Oct 20, 2021
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2 changes: 1 addition & 1 deletion Project.toml
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
name = "AdvancedMH"
uuid = "5b7e9947-ddc0-4b3f-9b55-0d8042f74170"
version = "0.6.5"
version = "0.6.6"

[deps]
AbstractMCMC = "80f14c24-f653-4e6a-9b94-39d6b0f70001"
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15 changes: 10 additions & 5 deletions README.md
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Expand Up @@ -111,14 +111,19 @@ rw_prop = RandomWalkProposal(Normal(0,1))
Different methods are easily composeable. One parameter can be static and another can be a random walk,
each of which may be drawn from separate distributions.

## Multithreaded sampling
## Multiple chains

AdvancedMH.jl implements the interface of [AbstractMCMC](https://github.com/TuringLang/AbstractMCMC.jl/), which means you get multiple chain sampling
in parallel for free:
AdvancedMH.jl implements the interface of [AbstractMCMC](https://github.com/TuringLang/AbstractMCMC.jl/) which means sampling of multiple chains is supported for free:

```julia
# Sample 4 chains from the posterior.
chain = psample(model, RWMH(init_params), 100000, 4; param_names=["μ","σ"], chain_type=Chains)
# Sample 4 chains from the posterior serially, without thread or process parallelism.
chain = sample(model, RWMH(init_params), MCMCSerial(), 100000, 4; param_names=["μ","σ"], chain_type=Chains)

# Sample 4 chains from the posterior using multiple threads.
chain = sample(model, RWMH(init_params), MCMCThreads(), 100000, 4; param_names=["μ","σ"], chain_type=Chains)

# Sample 4 chains from the posterior using multiple processes.
chain = sample(model, RWMH(init_params), MCMCDistributed(), 100000, 4; param_names=["μ","σ"], chain_type=Chains)
```

## Metropolis-adjusted Langevin algorithm (MALA)
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2 changes: 1 addition & 1 deletion src/AdvancedMH.jl
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Expand Up @@ -22,7 +22,7 @@ export
MALA

# Reexports
export sample, MCMCThreads, MCMCDistributed
export sample, MCMCThreads, MCMCDistributed, MCMCSerial

# Abstract type for MH-style samplers. Needs better name?
abstract type MHSampler <: AbstractMCMC.AbstractSampler end
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