| Copyright | (c) Adam Scibior 2015-2020 |
|---|---|
| License | MIT |
| Maintainer | leonhard.markert@tweag.io |
| Stability | experimental |
| Portability | GHC |
| Safe Haskell | None |
| Language | Haskell2010 |
Control.Monad.Bayes.Population
Description
Population turns a single sample into a collection of weighted samples.
Synopsis
- data Population m a
- runPopulation :: Functor m => Population m a -> m [(a, Log Double)]
- explicitPopulation :: Functor m => Population m a -> m [(a, Double)]
- fromWeightedList :: Monad m => m [(a, Log Double)] -> Population m a
- spawn :: Monad m => Int -> Population m ()
- resampleMultinomial :: MonadSample m => Population m a -> Population m a
- resampleSystematic :: MonadSample m => Population m a -> Population m a
- extractEvidence :: Monad m => Population m a -> Population (Weighted m) a
- pushEvidence :: MonadCond m => Population m a -> Population m a
- proper :: MonadSample m => Population m a -> Weighted m a
- evidence :: Monad m => Population m a -> m (Log Double)
- collapse :: MonadInfer m => Population m a -> m a
- mapPopulation :: Monad m => ([(a, Log Double)] -> m [(a, Log Double)]) -> Population m a -> Population m a
- normalize :: Monad m => Population m a -> Population m a
- popAvg :: Monad m => (a -> Double) -> Population m a -> m Double
- flatten :: Monad m => Population (Population m) a -> Population m a
- hoist :: (Monad m, Monad n) => (forall x. m x -> n x) -> Population m a -> Population n a
Documentation
data Population m a Source #
A collection of weighted samples, or particles.
Instances
runPopulation :: Functor m => Population m a -> m [(a, Log Double)] Source #
Explicit representation of the weighted sample with weights in the log domain.
explicitPopulation :: Functor m => Population m a -> m [(a, Double)] Source #
Explicit representation of the weighted sample.
fromWeightedList :: Monad m => m [(a, Log Double)] -> Population m a Source #
Initialize Population with a concrete weighted sample.
spawn :: Monad m => Int -> Population m () Source #
Increase the sample size by a given factor.
The weights are adjusted such that their sum is preserved.
It is therefore safe to use spawn in arbitrary places in the program
without introducing bias.
resampleMultinomial :: MonadSample m => Population m a -> Population m a Source #
Resample the population using the underlying monad and a multinomial resampling scheme. The total weight is preserved.
resampleSystematic :: MonadSample m => Population m a -> Population m a Source #
Resample the population using the underlying monad and a systematic resampling scheme. The total weight is preserved.
extractEvidence :: Monad m => Population m a -> Population (Weighted m) a Source #
Separate the sum of weights into the Weighted transformer.
Weights are normalized after this operation.
pushEvidence :: MonadCond m => Population m a -> Population m a Source #
Push the evidence estimator as a score to the transformed monad. Weights are normalized after this operation.
proper :: MonadSample m => Population m a -> Weighted m a Source #
A properly weighted single sample, that is one picked at random according to the weights, with the sum of all weights.
evidence :: Monad m => Population m a -> m (Log Double) Source #
Model evidence estimator, also known as pseudo-marginal likelihood.
collapse :: MonadInfer m => Population m a -> m a Source #
Picks one point from the population and uses model evidence as a score
in the transformed monad.
This way a single sample can be selected from a population without
introducing bias.
mapPopulation :: Monad m => ([(a, Log Double)] -> m [(a, Log Double)]) -> Population m a -> Population m a Source #
Applies a random transformation to a population.
normalize :: Monad m => Population m a -> Population m a Source #
Normalizes the weights in the population so that their sum is 1. This transformation introduces bias.
popAvg :: Monad m => (a -> Double) -> Population m a -> m Double Source #
Population average of a function, computed using unnormalized weights.
flatten :: Monad m => Population (Population m) a -> Population m a Source #
Combine a population of populations into a single population.
hoist :: (Monad m, Monad n) => (forall x. m x -> n x) -> Population m a -> Population n a Source #
Applies a transformation to the inner monad.