Description

Monadic wrapper for `CondesedTable`.

Synopsis

# Condensed tables

data CondensedTable v a

A lookup table for arbitrary discrete distributions. It allows the generation of random variates in O(1). Note that probability is quantized in units of `1/2^32`, and all distributions with infinite support (e.g. Poisson) should be truncated.

A `CondensedTable` that uses boxed vectors, and is able to hold any type of element.

A `CondensedTable` that uses unboxed vectors.

# Constructors for tables

tableFromProbabilities :: (Vector v (a, Word32), Vector v (a, Double), Vector v a, Vector v Word32, Show a) => v (a, Double) -> CondensedTable v a

Generate a condensed lookup table from a list of outcomes with given probabilities. The vector should be non-empty and the probabilites should be non-negative and sum to 1. If this is not the case, this algorithm will construct a table for some distribution that may bear no resemblance to what you intended.

tableFromWeights :: (Vector v (a, Word32), Vector v (a, Double), Vector v a, Vector v Word32, Show a) => v (a, Double) -> CondensedTable v a

Same as `tableFromProbabilities` but treats number as weights not probilities. Non-positive weights are discarded, and those remaining are normalized to 1.

tableFromIntWeights :: (Vector v (a, Word32), Vector v a, Vector v Word32) => v (a, Word32) -> CondensedTable v a

Generate a condensed lookup table from integer weights. Weights should sum to `2^32`. If they don't, the algorithm will alter the weights so that they do. This approach should work reasonably well for rounding errors.

## Disrete distributions

Create a lookup table for the Poisson distibution. Note that table construction may have significant cost. For λ < 100 it takes as much time to build table as generation of 1000-30000 variates.

tableBinomial

Arguments

 :: Int Number of tries -> Double Probability of success -> CondensedTableU Int

Create a lookup table for the binomial distribution.