scalation.stat

Statistic

class Statistic extends Error

The Statistic class is used to collect values and compute sample statistics on them (e.g., Waiting Time). Contrast with TimeStatistic defined below.

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Instance Constructors

  1. new Statistic(name: String = "stat", unbiased: Boolean = false)

    name

    the name for this statistic (e.g., WatingTime)

    unbiased

    whether the estimators are restricted to be unbiased

Value Members

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

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

    Definition Classes
    Any
  3. final def ##(): Int

    Definition Classes
    AnyRef → Any
  4. final def ==(arg0: AnyRef): Boolean

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

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  6. final def asInstanceOf[T0]: T0

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  7. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
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    @throws( ... )
  8. final def eq(arg0: AnyRef): Boolean

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

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    AnyRef → Any
  10. def finalize(): Unit

    Attributes
    protected[java.lang]
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    @throws( classOf[java.lang.Throwable] )
  11. def flaw(method: String, message: String): Unit

    Show the flaw by printing the error message.

    Show the flaw by printing the error message.

    method

    the method where the error occurred

    message

    the error message

    Definition Classes
    Error
  12. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  13. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  14. def interval(p: Double = .95): Double

    Compute the confidence interval half-width for the given confidence level.

    Compute the confidence interval half-width for the given confidence level.

    p

    the confidence level

  15. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  16. def max: Double

    Return the maximum value in sample.

  17. var maxX: Double

    The maximum sample value

    The maximum sample value

    Attributes
    protected
  18. def mean: Double

    Compute/estimate the sample mean.

  19. def min: Double

    Return the minimum value in sample.

  20. var minX: Double

    The minimum sample value

    The minimum sample value

    Attributes
    protected
  21. def ms: Double

    Compute/estimate the mean square (ms).

  22. var n: Int

    The number of samples

    The number of samples

    Attributes
    protected
  23. val name: String

    the name for this statistic (e.

    the name for this statistic (e.g., WatingTime)

  24. def nd: Double

    Return the number of samples as a double.

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

    Definition Classes
    AnyRef
  26. final def notify(): Unit

    Definition Classes
    AnyRef
  27. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  28. def num: Int

    Return the number of samples.

  29. def rms: Double

    Compute/estimate the root mean square (rms).

  30. def show: String

    Show the values of this collector's accumulators.

  31. def statRow: Array[AnyVal]

    Return the summary statistics as a row/Array.

  32. def stddev: Double

    Compute/estimate the sample standard deviation.

  33. var sum: Double

    Sum of the sample values

    Sum of the sample values

    Attributes
    protected
  34. var sumSq: Double

    Sum of the sample values squared

    Sum of the sample values squared

    Attributes
    protected
  35. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  36. def tally(x: Double): Unit

    Tally the next value and update accumulators.

    Tally the next value and update accumulators.

    x

    the value to tally

  37. def toString(): String

    Generate a row of statistical results as a string.

    Generate a row of statistical results as a string.

    Definition Classes
    Statistic → AnyRef → Any
  38. def variance: Double

    Compute/estimate the sample variance.

    Compute/estimate the sample variance. The denominator is one less for unbiased (n-1) vs. maximum likelihood (n) estimators. Also use n for population variance.

  39. final def wait(): Unit

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

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

    Definition Classes
    AnyRef
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    @throws( ... )

Inherited from Error

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