Class

org.hammerlab.stats

NonEmpty

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case class NonEmpty[K, V](n: V, sum: Double, mean: Double, stddev: Double, median: PercentileValue[K], mad: PercentileValue[K], samplesOpt: Option[Samples[K, V]], sortedSamplesOpt: Option[Samples[K, V]], percentiles: Percentiles[K])(implicit evidence$28: Numeric[K], evidence$29: Integral[V]) extends Stats[K, V] with Product with Serializable

Stores some computed statistics about a dataset of Numeric elements.

n

number of elements in the dataset.

mad

median absolute deviation (from the median).

samplesOpt

"sample" elements; the start and end of the data.

sortedSamplesOpt

"sample" elements; the least and greatest elements. If the dataset is already sorted, meaning this would be equivalent to samplesOpt, it is omitted.

percentiles

selected percentiles of the dataset.

Linear Supertypes
Serializable, Serializable, Product, Equals, Stats[K, V], AnyRef, Any
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  1. NonEmpty
  2. Serializable
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Instance Constructors

  1. new NonEmpty(n: V, sum: Double, mean: Double, stddev: Double, median: PercentileValue[K], mad: PercentileValue[K], samplesOpt: Option[Samples[K, V]], sortedSamplesOpt: Option[Samples[K, V]], percentiles: Percentiles[K])(implicit arg0: Numeric[K], arg1: Integral[V])

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    n

    number of elements in the dataset.

    mad

    median absolute deviation (from the median).

    samplesOpt

    "sample" elements; the start and end of the data.

    sortedSamplesOpt

    "sample" elements; the least and greatest elements. If the dataset is already sorted, meaning this would be equivalent to samplesOpt, it is omitted.

    percentiles

    selected percentiles of the dataset.

Value Members

  1. final def !=(arg0: Any): Boolean

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    AnyRef → Any
  2. final def ##(): Int

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    AnyRef → Any
  3. final def ==(arg0: Any): Boolean

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    AnyRef → Any
  4. final def asInstanceOf[T0]: T0

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  5. def clone(): AnyRef

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    protected[java.lang]
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    @throws( ... )
  6. final def eq(arg0: AnyRef): Boolean

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    AnyRef
  7. def finalize(): Unit

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    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )
  8. final def getClass(): Class[_]

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  9. final def isInstanceOf[T0]: Boolean

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  10. val mad: PercentileValue[K]

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    median absolute deviation (from the median).

  11. val mean: Double

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  12. val median: PercentileValue[K]

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  13. val n: V

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    number of elements in the dataset.

  14. final def ne(arg0: AnyRef): Boolean

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    AnyRef
  15. final def notify(): Unit

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  16. final def notifyAll(): Unit

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  17. val percentiles: Percentiles[K]

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    selected percentiles of the dataset.

  18. val samplesOpt: Option[Samples[K, V]]

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    "sample" elements; the start and end of the data.

  19. val sortedSamplesOpt: Option[Samples[K, V]]

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    "sample" elements; the least and greatest elements.

    "sample" elements; the least and greatest elements. If the dataset is already sorted, meaning this would be equivalent to samplesOpt, it is omitted.

  20. val stddev: Double

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  21. val sum: Double

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

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  23. final def wait(): Unit

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    @throws( ... )
  24. final def wait(arg0: Long, arg1: Int): Unit

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  25. final def wait(arg0: Long): Unit

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Inherited from Serializable

Inherited from Serializable

Inherited from Product

Inherited from Equals

Inherited from Stats[K, V]

Inherited from AnyRef

Inherited from Any

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