Packages

  • package root
    Definition Classes
    root
  • package mgo
    Definition Classes
    root
  • package abc

    Approximate Bayesian computation (ABC) methods are used to draw samples approximating a posterior distribution p(θ|y) ∝ p(y|θ) p(θ) when the value of the likelihood p(y|θ) is unavailable but one can sample according to the likelihood, typically via simulation.

    Approximate Bayesian computation (ABC) methods are used to draw samples approximating a posterior distribution p(θ|y) ∝ p(y|θ) p(θ) when the value of the likelihood p(y|θ) is unavailable but one can sample according to the likelihood, typically via simulation.

    Definition Classes
    mgo
  • package evolution
    Definition Classes
    mgo
  • package algorithm
  • C
  • D
  • RunAlgorithm
  • breeding
  • diversity
  • dominance
  • double2Scalable
  • elitism
  • niche
  • ranking
  • stop
  • package test
    Definition Classes
    mgo
  • package tools
    Definition Classes
    mgo
p

mgo

evolution

package evolution

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Package Members

  1. package algorithm

Type Members

  1. case class C(low: Double, high: Double) extends Product with Serializable
  2. case class D(low: Int, high: Int) extends Product with Serializable
  3. case class RunAlgorithm[T, I, G, S](t: T, algo: Algorithm[T, I, G, S], stopCondition: Option[StopCondition[S, I]] = None, traceOperation: Option[Trace[S, I]] = None) extends Product with Serializable
  4. type Trace[S, I] = (S, Vector[I]) => Unit
  5. class double2Scalable extends AnyRef

Value Members

  1. def afterGeneration[I, S](g: Long): StopCondition[EvolutionState[S], I]
  2. def anyReaches[M[_], I](goalReached: (I) => Boolean)(population: Vector[I])(implicit arg0: Monad[M]): (Vector[I]) => M[Boolean]

    ** Stop conditions ***

  3. def array2ToVectorLens[A](implicit arg0: Manifest[A]): Iso[Array[Array[A]], Vector[Vector[A]]]
  4. def arrayToVectorIso[A](implicit arg0: Manifest[A]): Iso[Array[A], Vector[A]]
  5. def changeScale(v: Double, fromMin: Double, fromMax: Double, toMin: Double, toMax: Double): Double
  6. implicit def double2Scalable(d: Double): double2Scalable
  7. def intToUnsignedIntOption: Iso[Int, Option[Int]]
  8. def newRNG(seed: Long): Random
  9. implicit def toAlgorithm[T, I, G, S](t: T)(implicit algo: Algorithm[T, I, G, S]): RunAlgorithm[T, I, G, S]
  10. object breeding
  11. object diversity

    Layer of the cake that compute a diversity metric for a set of values

  12. object dominance
  13. object elitism
  14. object niche
  15. object ranking
  16. object stop

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