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

   

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2. final def ##(): Int

   

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

   

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4. final def asInstanceOf[T0]: T0

   

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5. def bootstrap_CI(X: Seq[Double], statistic: (Seq[Double]) ⇒ Double, B: Int, alpha: Double): (Double, Double, Double)

   

   Returns the low bound, estimate, and high bound for a function of a random variable.

   Returns the low bound, estimate, and high bound for a function of a random variable.

   X

   A set of random variables.

   statistic

   A function from a set of random variables to a set of estimates.

   B

   The number of bootstrap replications.

   alpha

   The tolerable error.

   returns

   Low bound, estimate, and high bound.

6. def clone(): AnyRef

   

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

   

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8. def equals(arg0: Any): Boolean

   

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9. def finalize(): Unit

   

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

    

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11. def hashCode(): Int

    

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12. final def isInstanceOf[T0]: Boolean

    

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13. def multi_bootstrap_CI(X: Seq[Seq[Double]], statistic: (Seq[Seq[Double]]) ⇒ Double, B: Int, alpha: Double): (Double, Double, Double)

    

    Returns the low bound, estimate, and high bound for a function of a set of random variables.

    Returns the low bound, estimate, and high bound for a function of a set of random variables.

    X

    A set of random variables.

    statistic

    A function from a set of random variables to a set of estimates.

    B

    The number of bootstrap replications.

    alpha

    The tolerable error.

    returns

    Low bound, estimate, and high bound.

14. def multi_bootstrap_CIs(X: Seq[Seq[Double]], statistic: (Seq[Seq[Double]]) ⇒ Seq[Double], B: Int, alpha: Double): (Seq[Double], Seq[Double], Seq[Double])

    

    Returns a vector of low bounds, estimates, and high bounds for a function of a set of random variables.

    Returns a vector of low bounds, estimates, and high bounds for a function of a set of random variables.

    X

    A set of random variables.

    statistic

    A function from a set of random variables to a set of estimates.

    B

    The number of bootstrap replications.

    alpha

    The tolerable error.

    returns

    A vector of low bounds, estimates, and high bounds.

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

    

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16. final def notify(): Unit

    

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17. final def notifyAll(): Unit

    

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

    

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19. def toString(): String

    

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20. final def wait(): Unit

    

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

    

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

    

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