object Select

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  1. final def !=(arg0: Any): Boolean
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  2. final def ##(): Int
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  3. final def ==(arg0: Any): Boolean
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  4. def apply[T](parameter: AtomicDirichlet, outcomes: T*)(implicit name: Name[T], collection: ElementCollection): ParameterizedSelect[T]

    A distribution in which the probabilities are specified by a learnable parameter and the outcomes are values.

  5. def apply[T](probabilities: List[Element[Double]], outcomes: List[T])(implicit name: Name[T], collection: ElementCollection): CompoundSelect[T]

    A distribution in which the probabilities are Elements and the outcomes are values.

  6. def apply[T](clauses: (Element[Double], T)*)(implicit name: Name[T], collection: ElementCollection): CompoundSelect[T]

    A distribution in which the probabilities are Elements and the outcomes are values.

  7. def apply[T](probabilities: List[Double], outcomes: List[T])(implicit name: Name[T], collection: ElementCollection): AtomicSelect[T]

    A distribution in which both the probabilities and the outcomes are values.

    A distribution in which both the probabilities and the outcomes are values. Each outcome is chosen with the corresponding probability.

  8. def apply[T](clauses: (Double, T)*)(implicit name: Name[T], collection: ElementCollection): AtomicSelect[T]

    A distribution in which both the probabilities and the outcomes are values.

    A distribution in which both the probabilities and the outcomes are values. Each outcome is chosen with the corresponding probability.

  9. def apply[T](parameter: ParameterType, outcomes: T*)(implicit name: Name[T], collection: ElementCollection): Select[Double, T] with HasDensity[T]
  10. final def asInstanceOf[T0]: T0
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  11. def clone(): AnyRef
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  12. final def eq(arg0: AnyRef): Boolean
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  14. def finalize(): Unit
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  18. final def ne(arg0: AnyRef): Boolean
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  19. final def notify(): Unit
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  21. final def synchronized[T0](arg0: ⇒ T0): T0
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