org.hammerlab.stats

Stats

case class Stats[K, V](n: V, mean: Double, stddev: Double, mad: Double, samplesOpt: Option[Samples[K, V]], sortedSamplesOpt: Option[Samples[K, V]], percentiles: Seq[(Double, Double)])(implicit evidence$1: Numeric[K], evidence$2: Integral[V]) extends Product with Serializable

Wrapper for some computed statistics about a dataset of Numeric elements.

K

Numeric element type. TODO(ryan): allow this to be non-Numeric.

V

Integral value type.

n

number of elements in the dataset.

mean

mean.

stddev

stddev.

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.

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Instance Constructors

  1. new Stats(n: V, mean: Double, stddev: Double, mad: Double, samplesOpt: Option[Samples[K, V]], sortedSamplesOpt: Option[Samples[K, V]], percentiles: Seq[(Double, Double)])(implicit arg0: Numeric[K], arg1: Integral[V])

    n

    number of elements in the dataset.

    mean

    mean.

    stddev

    stddev.

    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: AnyRef): Boolean

    Definition Classes
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  2. final def !=(arg0: Any): Boolean

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  3. final def ##(): Int

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  4. final def ==(arg0: AnyRef): Boolean

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  5. final def ==(arg0: Any): Boolean

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  6. final def asInstanceOf[T0]: T0

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  7. def clone(): AnyRef

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    protected[java.lang]
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    @throws( ... )

  8. final def eq(arg0: AnyRef): Boolean

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  9. def finalize(): Unit

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    @throws( classOf[java.lang.Throwable] )

  10. final def getClass(): Class[_]

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  11. final def isInstanceOf[T0]: Boolean

    Definition Classes
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  12. val mad: Double

    median absolute deviation (from the median).

  13. val mean: Double

    mean.

  14. val n: V

    number of elements in the dataset.

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

    Definition Classes
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  16. final def notify(): Unit

    Definition Classes
    AnyRef

  17. final def notifyAll(): Unit

    Definition Classes
    AnyRef

  18. val percentiles: Seq[(Double, Double)]

    selected percentiles of the dataset.

  19. def prettyDouble(d: Double): String

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

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

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

    "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.

  22. val stddev: Double

    stddev.

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

    Definition Classes
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  24. def toString(): String

    Definition Classes
    Stats → AnyRef → Any

  25. final def wait(): Unit

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

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

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Inherited from Serializable

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