DiscreteRVWithDistr

abstract val underlyingDist: Distr

The actual probability density function is represented as a breeze Density object.

final def !=(arg0: Any): Boolean

final def ##(): Int

def :*[OtherDomain, OtherDistr <: DiscreteDistr[OtherDomain]](other: DiscreteRVWithDistr[OtherDomain, OtherDistr]): DiscreteRVWithDistr[(Domain, OtherDomain), DiscreteDistr[(Domain, OtherDomain)]]

def :*[Domain1, Dist1 <: Density[Domain1] with Rand[Domain1]](other: RandomVarWithDistr[Domain1, Dist1]): RandomVarWithDistr[(Domain, Domain1), GenericDistribution[(Domain, Domain1)]]

Cartesian product with another random variables which has a defined probability distribution.

def :*[Domain1](other: RandomVariable[Domain1]): RandomVariable[(Domain, Domain1)]

Outputs the cartesian product between two random variables.

final def ==(arg0: Any): Boolean

def >[OtherDomain](transformation: DataPipe[Domain, OtherDomain]): MeasurableFunction[Domain, OtherDomain, RandomVariable[Domain]]

Transform the current random variable on Domain to a morphed random variable on OtherDomain

final def asInstanceOf[T0]: T0

def clone(): AnyRef

def draw: Domain

Alias for sample.run()

final def eq(arg0: AnyRef): Boolean

def equals(arg0: Any): Boolean

def finalize(): Unit

final def getClass(): Class[_]

def hashCode(): Int

def iid(n: Int): IIDDiscreteRVDistr[Domain, Distr, DiscreteRVWithDistr.this.type]

Create an iid random variable from the current (this)

final def isInstanceOf[T0]: Boolean

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

val sample: DataPipe[Unit, Domain]

Generate a sample from the random variable

final def synchronized[T0](arg0: ⇒ T0): T0

def toString(): String

final def wait(): Unit

final def wait(arg0: Long, arg1: Int): Unit

final def wait(arg0: Long): Unit