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.

Linear Supertypes
Error, AnyRef, Any
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  1. Statistic
  2. Error
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Visibility
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  2. Protected

Instance Constructors

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

    name

    the name for this statistic (e.g., 'waitingTime')

    unbiased

    whether the estimators are restricted to be unbiased

Value Members

  1. final def flaw(method: String, message: String): Unit
    Definition Classes
    Error
  2. 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

  3. def ma: Double

    Compute/estimate the mean absolue value (ma), e.g., Mean Absolute Error (MAE).

  4. def max: Double

    Return the maximum value in sample.

  5. def mean: Double

    Compute/estimate the sample mean.

  6. def min: Double

    Return the minimum value in sample.

  7. def ms: Double

    Compute/estimate the mean square (ms), e.g., Mean Square Error (MSE).

  8. val name: String
  9. def nd: Double

    Return the number of samples as a double.

  10. def num: Int

    Return the number of samples.

  11. def reset(): Unit
  12. def rms: Double

    Compute/estimate the root mean square (rms), e.g., Root Mean Square Error (RMSE).

  13. def show: String

    Show the values of this collector's accumulators.

  14. def statRow: Array[Any]

    Return the summary statistics as a row/Array.

  15. def stddev: Double

    Compute/estimate the sample standard deviation.

  16. def tally(x: Double): Unit

    Tally the next value and update accumulators.

    Tally the next value and update accumulators.

    x

    the value to tally

  17. 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
  18. 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.