BirthDeathNearlyCritical.hs

{-# LANGUAGE DeriveDataTypeable #-}
{-# LANGUAGE DeriveGeneric      #-}

{- |
   Module      :  ELynx.Distribution.BirthDeathNearlyCritical
   Description :  Birth and death distribution
   Copyright   :  (c) Dominik Schrempf 2018
   License     :  GPL-3

   Maintainer  :  dominik.schrempf@gmail.com
   Stability   :  unstable
   Portability :  portable

Creation date: Tue Feb 13 13:16:18 2018.

See Gernhard, T. (2008). The conditioned reconstructed process. Journal of
Theoretical Biology, 253(4), 769–778. http://doi.org/10.1016/j.jtbi.2008.04.005.

Distribution of the values of the point process such that it corresponds to
reconstructed trees under the birth and death process; nearly critical birth and
death process with lambda~mu.

Basically, this is a Taylor expansion of Eq. (2) and Eq. (3).

-}

module ELynx.Distribution.BirthDeathNearlyCritical
  ( BirthDeathNearlyCriticalDistribution(..)
  , cumulative
  , density
  , quantile
  ) where

import           Data.Data                (Data, Typeable)
import           GHC.Generics             (Generic)
import qualified Statistics.Distribution  as D

import           ELynx.Distribution.Types

-- | Distribution of the values of the point process such that it corresponds to
-- a reconstructed tree of the birth and death process.
data BirthDeathNearlyCriticalDistribution = BDNCD
  { bdncdTOr :: Time    -- ^ Time to origin of the tree.
  , bdncdLa  :: Rate    -- ^ Birth and death rate.
  , bdncdMu  :: Rate    -- ^ Birth and death rate.
  } deriving (Eq, Typeable, Data, Generic)

instance D.Distribution BirthDeathNearlyCriticalDistribution where
    cumulative = cumulative

-- | Cumulative distribution function section 2.1.2, second formula.
cumulative :: BirthDeathNearlyCriticalDistribution -> Time -> Double
cumulative (BDNCD t l m) s
  | s <= 0    = 0
  | s >  t    = 1
  | otherwise = o0 + o1
  where o0 = s * (1.0 + t*l) / t / (1.0 + s*l)
        o1 = (-s*s + s*t) * (m - l) / (2.0*t * (1.0 + s*l)**2)

instance D.ContDistr BirthDeathNearlyCriticalDistribution where
  density  = density
  quantile = quantile

-- | Density function section 2.1.2, first formula.
density :: BirthDeathNearlyCriticalDistribution -> Time -> Double
density (BDNCD t l m) s
  | s < 0     = 0
  | s > t     = 0
  | otherwise = o0 + o1
  where
    o0 = (1.0 + t*l) / (t * (1.0 + s*l)**2)
    o1 = (-2.0*s + t - s*t*l) * (m - l) / (2.0*t * (1.0 + s*l)**3)

-- | Inverted cumulative probability distribution 'cumulative'. See also
-- 'D.ContDistr'.
quantile :: BirthDeathNearlyCriticalDistribution -> Double -> Time
quantile (BDNCD t l m) p
  | p >= 0 && p <= 1 = res
  | otherwise        =
    error $ "PointProcess.quantile: p must be in [0,1] range. Got: " ++ show p ++ "."
 where
   den   = l*(-3.0 + 2.0*t*(-1.0+p)*l)+m
   t1    = (2.0 + t*(l - 4.0*p*l + m)) / den
   t2Nom = 4.0 + t*(l*(4.0 + t*l + 8.0*p*(1.0 + t*l)) + 2.0*(2.0 + t*l - 4.0*p*(1.0 + t*l))*m + t*m*m)
   t2    = t2Nom / (den**2)
   res   = 0.5 * (t1 + sqrt t2)

instance D.ContGen BirthDeathNearlyCriticalDistribution where
  genContVar = D.genContinuous