GenericContinuousMCMC

Instance Constructors

new GenericContinuousMCMC(p: ContinuousRVWithDistr[ConditioningSet, ContinuousDistr[ConditioningSet]], c: DataPipe[ConditioningSet, ContinuousRVWithDistr[Domain, ContinuousDistr[Domain]]], proposalDist: ContinuousRVWithDistr[ConditioningSet, ContinuousDistr[ConditioningSet]], burnIn: Long = 1000L, dropCount: Int = 100)(implicit vectorSpace: Field[ConditioningSet])

p
The prior distribution on model parameters as a DynaML random variable
c
The likelihood of the data given a particular value of parameters

Value Members

final def !=(arg0: Any): Boolean

Definition Classes
AnyRef → Any
final def ##(): Int

Definition Classes
AnyRef → Any
def :*[Domain1, Dist1 <: Density[Domain1] with Rand[Domain1]](other: RandomVarWithDistr[Domain1, Dist1]): RandomVarWithDistr[((ConditioningSet, Domain), Domain1), GenericDistribution[((ConditioningSet, Domain), Domain1)]]

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

Definition Classes
RandomVarWithDistr
def :*[Domain1](other: RandomVariable[Domain1]): RandomVariable[((ConditioningSet, Domain), Domain1)]

Outputs the cartesian product between two random variables.
Outputs the cartesian product between two random variables.
Domain1
The domain of the other random variable
other
The random variable which forms the second component of the cartesian product.

Definition Classes
RandomVariable
final def ==(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def >[OtherDomain](transformation: DataPipe[(ConditioningSet, Domain), OtherDomain]): MeasurableFunction[(ConditioningSet, Domain), OtherDomain, RandomVariable[(ConditioningSet, Domain)]]

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

Definition Classes
RandomVariable
var Max_Candidates: Int

Definition Classes
RejectionSamplingScheme
var Max_Estimations: Int

Definition Classes
RejectionSamplingScheme
final def asInstanceOf[T0]: T0

Definition Classes
Any
def clone(): AnyRef

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( ... )
def draw: (ConditioningSet, Domain)

Alias for sample.run()
Alias for sample.run()

Definition Classes
RandomVariable
final def eq(arg0: AnyRef): Boolean

Definition Classes
AnyRef
def equals(arg0: Any): Boolean

Definition Classes
AnyRef → Any
def finalize(): Unit

Attributes
protected[java.lang]
Definition Classes
AnyRef
Annotations
@throws( classOf[java.lang.Throwable] )
final def getClass(): Class[_]

Definition Classes
AnyRef → Any
def hashCode(): Int

Definition Classes
AnyRef → Any
def iid(n: Int): RandomVariable[Stream[(ConditioningSet, Domain)]] with IIDRandomVariable[(ConditioningSet, Domain), RandomVarWithDistr[(ConditioningSet, Domain), AbstractContinuousDistr[(ConditioningSet, Domain)]]]

Create an iid random variable from the current (this)
Create an iid random variable from the current (this)
n
The number of iid samples of the base random variable.

Definition Classes
RandomVarWithDistr → RandomVariable
final def isInstanceOf[T0]: Boolean

Definition Classes
Any
val likelihood: DataPipe[ConditioningSet, RandomVarWithDistr[Domain, ContinuousDistr[Domain]]]

Definition Classes
RejectionSamplingScheme → JointProbabilityScheme
final def ne(arg0: AnyRef): Boolean

Definition Classes
AnyRef
final def notify(): Unit

Definition Classes
AnyRef
final def notifyAll(): Unit

Definition Classes
AnyRef
val posterior: DataPipe[Domain, RandomVariable[ConditioningSet]]

Definition Classes
GenericContinuousMCMC → RejectionSamplingScheme → BayesJointProbabilityScheme
val prior: RandomVarWithDistr[ConditioningSet, ContinuousDistr[ConditioningSet]]

Definition Classes
RejectionSamplingScheme → JointProbabilityScheme
val sample: DataPipe[Unit, (ConditioningSet, Domain)]

Generate a sample from the random variable
Generate a sample from the random variable

Definition Classes
RejectionSamplingScheme → JointProbabilityScheme → RandomVariable
final def synchronized[T0](arg0: ⇒ T0): T0

Definition Classes
AnyRef
def toString(): String

Definition Classes
AnyRef → Any
val underlyingDist: AbstractContinuousDistr[(ConditioningSet, Domain)]

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

Definition Classes
GenericContinuousMCMC → RandomVarWithDistr → HasDistribution
final def wait(): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long, arg1: Int): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )
final def wait(arg0: Long): Unit

Definition Classes
AnyRef
Annotations
@throws( ... )

Inherited from RejectionSamplingScheme[ConditioningSet, Domain, ContinuousDistr[ConditioningSet], ContinuousDistr[Domain], AbstractContinuousDistr[(ConditioningSet, Domain)]]

Inherited from BayesJointProbabilityScheme[ConditioningSet, Domain, RandomVarWithDistr[ConditioningSet, ContinuousDistr[ConditioningSet]], RandomVarWithDistr[Domain, ContinuousDistr[Domain]]]

Inherited from JointProbabilityScheme[ConditioningSet, Domain, RandomVarWithDistr[ConditioningSet, ContinuousDistr[ConditioningSet]], RandomVarWithDistr[Domain, ContinuousDistr[Domain]]]

Related Doc: package probability

class GenericContinuousMCMC[ConditioningSet, Domain] extends RejectionSamplingScheme[ConditioningSet, Domain, ContinuousDistr[ConditioningSet], ContinuousDistr[Domain], AbstractContinuousDistr[(ConditioningSet, Domain)]]

Instance Constructors

Value Members

final def !=(arg0: Any): Boolean

final def ##(): Int

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

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

final def ==(arg0: Any): Boolean

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

var Max_Candidates: Int

var Max_Estimations: Int

final def asInstanceOf[T0]: T0

def clone(): AnyRef

def draw: (ConditioningSet, Domain)

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): RandomVariable[Stream[(ConditioningSet, Domain)]] with IIDRandomVariable[(ConditioningSet, Domain), RandomVarWithDistr[(ConditioningSet, Domain), AbstractContinuousDistr[(ConditioningSet, Domain)]]]

final def isInstanceOf[T0]: Boolean

val likelihood: DataPipe[ConditioningSet, RandomVarWithDistr[Domain, ContinuousDistr[Domain]]]

final def ne(arg0: AnyRef): Boolean

final def notify(): Unit

final def notifyAll(): Unit

val posterior: DataPipe[Domain, RandomVariable[ConditioningSet]]

val prior: RandomVarWithDistr[ConditioningSet, ContinuousDistr[ConditioningSet]]

val sample: DataPipe[Unit, (ConditioningSet, Domain)]

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

def toString(): String

val underlyingDist: AbstractContinuousDistr[(ConditioningSet, Domain)]

final def wait(): Unit

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

final def wait(arg0: Long): Unit

Inherited from RejectionSamplingScheme[ConditioningSet, Domain, ContinuousDistr[ConditioningSet], ContinuousDistr[Domain], AbstractContinuousDistr[(ConditioningSet, Domain)]]

Inherited from BayesJointProbabilityScheme[ConditioningSet, Domain, RandomVarWithDistr[ConditioningSet, ContinuousDistr[ConditioningSet]], RandomVarWithDistr[Domain, ContinuousDistr[Domain]]]

Inherited from JointProbabilityScheme[ConditioningSet, Domain, RandomVarWithDistr[ConditioningSet, ContinuousDistr[ConditioningSet]], RandomVarWithDistr[Domain, ContinuousDistr[Domain]]]

Inherited from RandomVarWithDistr[(ConditioningSet, Domain), AbstractContinuousDistr[(ConditioningSet, Domain)]]

Inherited from HasDistribution[(ConditioningSet, Domain)]

Inherited from RandomVariable[(ConditioningSet, Domain)]

Inherited from Serializable

Inherited from Serializable

Inherited from AnyRef

Inherited from Any

Ungrouped