scalation.stat

BatchVec

class BatchVec extends AnyRef

This class contains a Random Vector (RVec) for maintaining experimental data in multiple batches and methods for computing statistics on these data. Ex: It may be used to implement the Method of Batch Means (MBM) in simulation.

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  1. BatchVec
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Instance Constructors

  1. new BatchVec(name: String, _bSize: Int = 10, _nBatches: Int = 10)

    name

    name of the batch statistic

    _bSize

    size of each batch

    _nBatches

    number of batches

Value Members

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

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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. def allocBatches(more: Int = 1): Unit

    Allocate additional batches for this batched vector.

    Allocate additional batches for this batched vector.

    more

    the number of additional batches to allocate

  7. final def asInstanceOf[T0]: T0

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  8. def autoCorr: Double

    Compute the average autocorrelation between all of the batches.

    Compute the average autocorrelation between all of the batches. FIX: implement correctly using Rvec methods

  9. def bSize: Int

    Get the batch size.

  10. def clone(): AnyRef

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

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  12. def equals(arg0: Any): Boolean

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  13. def finalize(): Unit

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  14. final def getClass(): java.lang.Class[_]

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  15. def hashCode(): Int

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  16. final def isInstanceOf[T0]: Boolean

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  17. def len: Int

    Get the total length of the batched vector.

  18. def nBatches: Int

    Get the number of batches.

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

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  20. final def notify(): Unit

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  21. final def notifyAll(): Unit

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  22. def precise(precision: Double = .2): Boolean

    Determine if the Confidence Interval (CI) on the grand mean is tight enough.

    Determine if the Confidence Interval (CI) on the grand mean is tight enough. FIX: implement correctly using Rvec methods

    precision

    the cut-off value for CI to be considered tight

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

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  24. def tally(value: Double): Unit

    Add the given value in the next index position in the batched vector.

    Add the given value in the next index position in the batched vector.

    value

    the given value to add

  25. def toString(): String

    Convert the batched vector into a string showing each of the batches.

    Convert the batched vector into a string showing each of the batches.

    Definition Classes
    BatchVec → AnyRef → Any
  26. def uncorrelated(threshold: Double = .2): Boolean

    Determine if the batches are sufficiently uncorrelated.

    Determine if the batches are sufficiently uncorrelated.

    threshold

    the cut-off value to be considered uncorrelated

  27. final def wait(): Unit

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

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

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