class AtomicBeta extends Element[Double] with HasDensity[Double] with NormalProposer with DoubleParameter with Beta

A Beta distribution in which the alpha and beta parameters are provided. This Beta element can be used as the parameter for a ParameterizedFlip.

Linear Supertypes
Beta, Continuous[Double], DoubleParameter, Parameter[Double], NormalProposer, Atomic[Double], HasDensity[Double], Element[Double], AnyRef, Any
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Inherited
  1. AtomicBeta
  2. Beta
  3. Continuous
  4. DoubleParameter
  5. Parameter
  6. NormalProposer
  7. Atomic
  8. HasDensity
  9. Element
  10. AnyRef
  11. Any
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Visibility
  1. Public
  2. All

Instance Constructors

  1. new AtomicBeta(name: Name[Double], a: Double, b: Double, collection: ElementCollection)

    a

    The prior alpha parameter

    b

    The prior beta parameter

Type Members

  1. type Condition = (Double) ⇒ Boolean

    The type of conditions on the element.

    The type of conditions on the element. A condition is a function from a value to a Boolean.

    Definition Classes
    Element
  2. type Constraint = (Double) ⇒ Double

    The type of soft constraints on the element.

    The type of soft constraints on the element. A constraint is a function from a value to a Double.

    Definition Classes
    Element
  3. type Randomness = Double

    The type of randomness content of the element.

    The type of randomness content of the element.

    Definition Classes
    NormalProposerElement
  4. type Value = Double

    The type of values over which the element is defined.

    The type of values over which the element is defined.

    Definition Classes
    Element

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. def !==(that: Element[Value])(implicit universe: Universe): Neq[Value]

    The element that tests inequality of this element with another element.

    The element that tests inequality of this element with another element.

    Definition Classes
    Element
  3. final def ##(): Int
    Definition Classes
    AnyRef → Any
  4. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  5. def ===(that: Value)(implicit universe: Universe): Apply1[Double, Boolean]

    The element that tests whether the value of this element is equal to a particular value.

    The element that tests whether the value of this element is equal to a particular value.

    Definition Classes
    Element
  6. def ===(that: Element[Value])(implicit universe: Universe): Eq[Value]

    The element that tests equality of this element with another element.

    The element that tests equality of this element with another element.

    Definition Classes
    Element
  7. def MAPValue: Double

    The most likely value of the parameter (maximum a posteriori) given the evidence.

    The most likely value of the parameter (maximum a posteriori) given the evidence.

    Definition Classes
    AtomicBetaParameter
  8. def aValue: Double

    Current a value.

    Current a value.

    Definition Classes
    AtomicBetaBeta
  9. def activate(): Unit

    Activate the element in its universe.

    Activate the element in its universe.

    Definition Classes
    Element
  10. var active: Boolean

    Flag indicating whether the element is currently active in its universe.

    Flag indicating whether the element is currently active in its universe.

    Definition Classes
    Element
  11. def addCondition(condition: Condition, contingency: Contingency = List()): Unit

    Add the given condition to the existing conditions of the element.

    Add the given condition to the existing conditions of the element. By default, the contingency is empty.

    Definition Classes
    Element
  12. def addConstraint(constraint: Constraint, contingency: Contingency = List()): Unit

    Add a contingent constraint to the element.

    Add a contingent constraint to the element. By default, the contingency is empty.

    Definition Classes
    Element
  13. def addLogConstraint(constraint: Constraint, contingency: Contingency = List()): Unit

    Add a log contingent constraint to the element.

    Add a log contingent constraint to the element. By default, the contingency is empty.

    Definition Classes
    Element
  14. def addPragma(pragma: Pragma[Value]): Unit

    Add a pragma to the element.

    Add a pragma to the element.

    Definition Classes
    Element
  15. def allConditions: List[(Condition, Contingency)]

    All the conditions defined on this element.

    All the conditions defined on this element.

    Definition Classes
    Element
  16. def allConstraints: List[(Constraint, Contingency)]

    The current soft constraints on the element.

    The current soft constraints on the element.

    Definition Classes
    Element
  17. def args: List[Element[_]]

    Returns an empty list.

    Returns an empty list.

    Definition Classes
    AtomicElement
  18. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  19. def bValue: Double

    Current b value.

    Current b value.

    Definition Classes
    AtomicBetaBeta
  20. def clearContext(): Unit

    Clears all the temporary elements associated with this element (all elements created in it's context).

    Clears all the temporary elements associated with this element (all elements created in it's context).

    Definition Classes
    Element
  21. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  22. val collection: ElementCollection
    Definition Classes
    Element
  23. def condition(value: Any): Boolean

    Tests whether all the element's contingent conditions are satisfied for the given value.

    Tests whether all the element's contingent conditions are satisfied for the given value.

    Definition Classes
    Element
  24. def conditionSatisfied: Boolean

    Determines whether the condition on the element is satisfied by the current value.

    Determines whether the condition on the element is satisfied by the current value.

    Definition Classes
    Element
  25. def constraint(value: Any): Double

    Gets the result of all the element's contingent constraints for the given value.

    Gets the result of all the element's contingent constraints for the given value.

    Definition Classes
    Element
  26. def constraintValue: Double

    Determines the value of the constraint on the element applied to the current value.

    Determines the value of the constraint on the element applied to the current value.

    Definition Classes
    Element
  27. def context: List[Element[_]]

    The elements on which the existence of this element depends.

    The elements on which the existence of this element depends.

    Definition Classes
    Element
  28. def deactivate(): Unit

    Deactivate the element in its universe.

    Deactivate the element in its universe.

    Definition Classes
    Element
  29. def density(x: Double): Double

    Density of a value.

    Density of a value.

    Definition Classes
    AtomicBetaHasDensity
  30. def directContextContents: Set[Element[_]]

    Returns the set of elements directly created in the context of this element.

    Returns the set of elements directly created in the context of this element.

    Definition Classes
    Element
  31. def elementsIAmContingentOn: Set[Element[_]]

    Returns the elements that this element is contingent on.

    Returns the elements that this element is contingent on. These are elements that are required to have a certain value for a condition or constraint to be relevant to this element. The contingency is required because conditions and constraints can be applied to references that are uncertain. Every possible element that could be pointed to by a reference must be given the condition or constraint, but the condition or constraint only applies if the elements earlier in the reference have the required value.

    Figaro takes care of handling all this under the hood. However, some algorithms may need to know which elements an element is contingent on. For example, sampling algorithms may need to sample those other elements first. This method is supplied to support this use case.

    Definition Classes
    Element
  32. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  33. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  34. def expectedValue: Double

    The expected value of the parameter.

    The expected value of the parameter.

    Definition Classes
    AtomicBetaParameter
  35. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  36. def flatMap[U](fn: (Value) ⇒ Element[U])(implicit name: Name[U], collection: ElementCollection): Element[U]
    Definition Classes
    Element
  37. final def generate(): Unit

    First generate the randomness, then generate the value given the randomness.

    First generate the randomness, then generate the value given the randomness. Store the results in randomness and value.

    Definition Classes
    Element
  38. def generateRandomness(): Double

    Generate the randomness content.

    Generate the randomness content.

    Definition Classes
    AtomicBetaElement
  39. def generateValue(rand: Randomness): Randomness

    A strictly monotone differentiable function defined on (lower, upper).

    A strictly monotone differentiable function defined on (lower, upper). Defaults to the identity function.

    Definition Classes
    NormalProposerElement
  40. def generateValueDerivative(rand: Randomness): Double

    The absolute value of the derivative of generateValue with respect to the randomness given.

    The absolute value of the derivative of generateValue with respect to the randomness given. This is needed to compute a proposal density over the transformed randomness. Defaults to 1.0, corresponding to the case where generateValue is the identity function.

    Definition Classes
    NormalProposer
  41. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
  42. val hashCode: Int
    Definition Classes
    Element
  43. def intervene(v: Value): Unit
    Definition Classes
    Element
  44. def isCachable(): Boolean

    The cacheability of the element.

    The cacheability of the element. Chains create caches of their parent values, and it is useful to know when these values can be effectively cached and reused. In general, continuous distributions are not cacheable.

    Definition Classes
    Element
  45. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  46. def isTemporary: Boolean

    Returns true if this element is temporary, that is, was created in the context of another element.

    Returns true if this element is temporary, that is, was created in the context of another element.

    Definition Classes
    Element
  47. var learnedAlpha: Double

    The learned alpha parameter

  48. var learnedBeta: Double

    The learned beta parameter

  49. def logp(value: Double): Double

    Log-likelihood of a value.

    Log-likelihood of a value.

    Definition Classes
    BetaContinuous
  50. def lower: Double

    Exclusive lower bound of the range of the randomness of this element.

    Exclusive lower bound of the range of the randomness of this element. Defaults to -Infinity. Must be strictly less than the upper bound.

    Definition Classes
    AtomicBetaNormalProposer
  51. def makeValues(depth: Int): ValueSet[Double]
  52. def map[U](fn: (Value) ⇒ U)(implicit name: Name[U], collection: ElementCollection): Element[U]
    Definition Classes
    Element
  53. def maximize(sufficientStatistics: Seq[Double]): Unit

    Sets the hyperparameters of this parameter to their most likely value based on the sufficient statistics provided.

    Sets the hyperparameters of this parameter to their most likely value based on the sufficient statistics provided.

    Definition Classes
    AtomicBetaParameter
  54. val name: Name[Double]
    Definition Classes
    Element
  55. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  56. def nextRandomness(oldRandomness: Randomness): (Randomness, Double, Double)

    Generate the next randomness given the current randomness.

    Generate the next randomness given the current randomness. Returns three values: The next randomness, the Metropolis-Hastings proposal probability ratio, which is:

    P(new -> old) / P(old -> new)

    and the model probability ratio, which is:

    P(new) / P(old)

    By default, this implementation proposes a normally distributed randomness from the previous randomness, truncated to be within the appropriate range. The probability ratios returned are associated with the values of this element rather than the randomness. This is for the purpose of simulated annealing, since the most likely randomness is not necessarily the most likely value, depending on the form of the generateValue function.

    One can override this to only use normal proposals in certain special cases.

    Definition Classes
    AtomicBetaNormalProposerHasDensityElement
  57. final def normalNextRandomness(oldRandomness: Randomness): (Randomness, Double, Double)

    Computes the normal proposal for nextRandomness.

    Computes the normal proposal for nextRandomness. This is separated from the nextRandomness so that subclasses can choose when to use normal proposals.

    Attributes
    protected
    Definition Classes
    NormalProposer
    Annotations
    @tailrec()
  58. val normalizer: Double

    The normalizing factor.

  59. final def notify(): Unit
    Definition Classes
    AnyRef
  60. final def notifyAll(): Unit
    Definition Classes
    AnyRef
  61. def observe(observation: Value): Unit

    Condition the element by observing a particular value.

    Condition the element by observing a particular value. Propagates the effect to dependent elements and ensures that no other value for the element can be generated.

    Definition Classes
    Element
  62. def pragmas: List[Pragma[Value]]

    The pragmas attached to the element.

    The pragmas attached to the element.

    Definition Classes
    Element
  63. def proposalProb(oldRandomness: Double, newRandomness: Double): Double

    Computes the proposal probability density in one direction.

    Computes the proposal probability density in one direction. Both values should be in the interval (lower, upper).

    oldRandomness

    The previous randomness.

    newRandomness

    The newly proposed randomness.

    returns

    The probability density associated with the transition from generateValue(oldRandomness) to generateValue(newRandomness). This is a density over the corresponding values (as opposed to randomnesses).

    Attributes
    protected
    Definition Classes
    NormalProposer
  64. def proposalScale: Double

    The scale of the normally distributed proposal.

    The scale of the normally distributed proposal. This corresponds to the standard deviation of the proposal before truncation. If the randomness has finite variance, this should be less than or equal to its standard deviation. A good place to start is e.g. 20% of the standard deviation.

    Definition Classes
    AtomicBetaNormalProposer
  65. var randomness: Randomness

    The current randomness content of the element.

    The current randomness content of the element.

    Definition Classes
    Element
  66. def removeConditions(contingency: Contingency = List()): Unit

    Remove all conditions associated with the given contingency.

    Remove all conditions associated with the given contingency. By default, the contingency is empty.

    Definition Classes
    Element
  67. def removeConstraint(constraint: Constraint, contingency: Contingency = List()): Unit
    Attributes
    protected
    Definition Classes
    Element
  68. def removeConstraints(contingency: Contingency = List()): Unit

    Remove all constraints associated with the given contingency.

    Remove all constraints associated with the given contingency. By default, the contingency is empty.

    Definition Classes
    Element
  69. def removePragma(pragma: Pragma[Value]): Unit

    Remove a pragma from the element.

    Remove a pragma from the element.

    Definition Classes
    Element
  70. def score(oldValue: Value, newValue: Value): Double

    Compute the constraints on the new value divided by the constraints on the old value.

    Compute the constraints on the new value divided by the constraints on the old value.

    Definition Classes
    Element
  71. def set(newValue: Value): Unit

    Set the value of this element and propagate the effects to elements that depend on it without changing their randomness.

    Set the value of this element and propagate the effects to elements that depend on it without changing their randomness. Also disallows the value of the element to change until unobserve or unset is called.

    Definition Classes
    Element
  72. def setCondition(newCondition: Condition, contingency: Contingency = List()): Unit

    Set the condition associated with the contingency.

    Set the condition associated with the contingency. Removes previous conditions associated with the contingency. By default, the contingency is empty.

    Definition Classes
    Element
  73. def setConstraint(newConstraint: Constraint, contingency: Contingency = List()): Unit

    Set the constraint associated with the contingency.

    Set the constraint associated with the contingency. Removes previous constraints associated with the contingency. By default, the contingency is empty.

    Definition Classes
    Element
  74. def setLogConstraint(newConstraint: Constraint, contingency: Contingency = List()): Unit

    Set the log constraint associated with the contingency.

    Set the log constraint associated with the contingency. Removes previous constraints associated with the contingency. By default, the contingency is empty.

    Definition Classes
    Element
  75. def setRandomness(newRandomness: Randomness): Unit

    Set the randomness of this element.

    Set the randomness of this element.

    Will generate its value using the new randomness and propagate the effects to elements that depend on it without changing their randomness.

    Definition Classes
    Element
  76. def sufficientStatistics[Boolean](b: Boolean): Seq[Double]

    Returns a sufficient statistics vector corresponding to the evidence that an element using this parameter took on the value a.

    Returns a sufficient statistics vector corresponding to the evidence that an element using this parameter took on the value a.

    Definition Classes
    AtomicBetaParameter
  77. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  78. def toNameString: String

    A string that is the element's name, if it has a non-empty one, otherwise the result of the element's toString.

    A string that is the element's name, if it has a non-empty one, otherwise the result of the element's toString.

    Definition Classes
    Element
  79. def toString(): String
    Definition Classes
    AtomicBeta → AnyRef → Any
  80. def unintervene(): Unit
    Definition Classes
    Element
  81. val universe: Universe

    The universe in which the element is defined.

    The universe in which the element is defined.

    Definition Classes
    Element
  82. def unobserve(): Unit

    Removes conditions on the element and allows different values of the element to be generated.

    Removes conditions on the element and allows different values of the element to be generated.

    Definition Classes
    Element
  83. def unset(): Unit

    Allows different values of the element to be generated.

    Allows different values of the element to be generated.

    Definition Classes
    Element
  84. def upper: Double

    Exclusive upper bound of the range of the randomness of this element.

    Exclusive upper bound of the range of the randomness of this element. Defaults to Infinity. Must be strictly greater than the lower bound.

    Definition Classes
    AtomicBetaNormalProposer
  85. var value: Value

    The current value of the element.

    The current value of the element.

    Definition Classes
    Element
  86. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  87. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  88. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  89. def zeroSufficientStatistics(): Seq[Double]

    Returns an empty sufficient statistics vector.

    Returns an empty sufficient statistics vector.

    Definition Classes
    AtomicBetaParameter

Deprecated Value Members

  1. def getLearnedElement: AtomicFlip

    Returns an element that models the learned distribution.

    Returns an element that models the learned distribution.

    Deprecated

Inherited from Beta

Inherited from Continuous[Double]

Inherited from DoubleParameter

Inherited from Parameter[Double]

Inherited from NormalProposer

Inherited from Atomic[Double]

Inherited from HasDensity[Double]

Inherited from Element[Double]

Inherited from AnyRef

Inherited from Any

Ungrouped