diff --git a/Data/Sampling/Types.hs b/Data/Sampling/Types.hs
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+++ b/Data/Sampling/Types.hs
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+{-# OPTIONS_GHC -Wall #-}
+{-# LANGUAGE RecordWildCards #-}
+
+-- |
+-- Module: Data.Sampling.Types
+-- Copyright: (c) 2015 Jared Tobin
+-- License: MIT
+--
+-- Maintainer: Jared Tobin <jared@jtobin.ca>
+-- Stability: unstable
+-- Portability: ghc
+--
+-- Common types for implementing Markov Chain Monte Carlo (MCMC) algorithms.
+--
+-- 'Target' is a product type intended to hold a log-target density function and
+-- potentially its gradient.
+--
+-- The 'Chain' type represents a kind of annotated parameter space.
+-- Technically all that's required here is the type of the parameter space
+-- itself (held here in 'chainPosition') but in practice some additional
+-- information is typically useful.  Additionally there is 'chainScore' for
+-- holding the most recent score of the chain, as well as the target itself for
+-- implementing things like annealing.  The `chainTunables` field can be used
+-- to hold arbitrary data.
+--
+-- One should avoid exploiting these features to do something nasty (like, say,
+-- invalidating the Markov property).
+--
+-- The 'Transition' type permits probabilistic transitions over some state
+-- space by way of the underlying 'Prob' monad.
+
+module Data.Sampling.Types (
+    Transition
+  , Chain(..)
+  , Target(..)
+  ) where
+
+import Control.Monad.Trans.State.Strict (StateT)
+import System.Random.MWC.Probability (Prob)
+
+-- | A generic transition operator.
+--
+--   Has access to randomness via the underlying 'Prob' monad.
+type Transition m a = StateT a (Prob m) ()
+
+-- | The @Chain@ type specifies the state of a Markov chain at any given
+--   iteration.
+data Chain a b = Chain {
+    chainTarget   :: Target a
+  , chainScore    :: !Double
+  , chainPosition :: a
+  , chainTunables :: Maybe b
+  }
+
+instance Show a => Show (Chain a b) where
+  show Chain {..} = filter (`notElem` "fromList []") (show chainPosition)
+
+-- | A @Target@ consists of a function from parameter space to the reals, as
+--   well as possibly a gradient.
+--
+--   Most implementations assume a /log/-target, so records are named
+--   accordingly.
+data Target a = Target {
+    lTarget  :: a -> Double
+  , glTarget :: Maybe (a -> a)
+  }
+
diff --git a/LICENSE b/LICENSE
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--- /dev/null
+++ b/LICENSE
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+Copyright (c) 2015 Jared Tobin
+
+Permission is hereby granted, free of charge, to any person obtaining
+a copy of this software and associated documentation files (the
+"Software"), to deal in the Software without restriction, including
+without limitation the rights to use, copy, modify, merge, publish,
+distribute, sublicense, and/or sell copies of the Software, and to
+permit persons to whom the Software is furnished to do so, subject to
+the following conditions:
+
+The above copyright notice and this permission notice shall be included
+in all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
+MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
+IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY
+CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT,
+TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE
+SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
diff --git a/Setup.hs b/Setup.hs
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--- /dev/null
+++ b/Setup.hs
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+import Distribution.Simple
+main = defaultMain
diff --git a/mcmc-types.cabal b/mcmc-types.cabal
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--- /dev/null
+++ b/mcmc-types.cabal
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+name:                mcmc-types
+version:             1.0.0
+synopsis:            Common types for sampling.
+homepage:            http://github.com/jtobin/mcmc-types
+license:             MIT
+license-file:        LICENSE
+author:              Jared Tobin
+maintainer:          jared@jtobin.ca
+build-type:          Simple
+cabal-version:       >= 1.18
+description:
+  Common types for implementing Markov Chain Monte Carlo (MCMC) algorithms.
+  .
+  An instance of an MCMC problem can be characterized by the following:
+  .
+  * A /target distribution/ over some parameter space
+  .
+  * A /parameter space/ for a Markov chain to wander over
+  .
+  * A /transition operator/ to drive the Markov chain
+  .
+  /mcmc-types/ provides the suitably-general 'Target', 'Chain', and
+  'Transition' types for representing these things respectively.
+
+Source-repository head
+  Type:     git
+  Location: http://github.com/jtobin/mcmc-types.git
+
+library
+  exposed-modules:     Data.Sampling.Types
+  default-language:    Haskell2010
+  build-depends:
+      base            < 5
+    , containers
+    , mwc-probability >= 1.0.0
+    , transformers
+