MathFuncs

Value Members

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 avg(t: Seq[Double]): Double

   

   Computes the mean of a sequence of doubles

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. def freqToProb[A](implicit n: Numeric[A]): (TraversableOnce[A]) ⇒ TraversableOnce[Double]

    

    Converts frequencies to probabilities by normalizing each count by the vector sum.

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

    

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12. def hashCode(): Int

    

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13. def intBiG(muTuple: Pair[Double], sigmaTuple: Pair[Double], pTuple: Pair[Double])(x: Double): Double

    

    Cumulative distribution function of a bimodal Gaussian distribution.

    Cumulative distribution function of a bimodal Gaussian distribution.

    Given a pair of means and a pair of standard deviations for two Gaussian distributions; and a pair of weights specifying the balance of the two Gaussians, yields a function for evaluating the CDF of the bimodal distribution determined by these parameters.

    muTuple

    The means of the two Gaussians.

    sigmaTuple

    The standard deviations of the two Gaussians.

    pTuple

    The weights of the two Gaussians in the bimodal distribution.

    x

    Value for evaluating CDF(x)

    returns

    CDF(x) for the bimodal Gaussian distribution.

14. def intUniG(mu: Double, sigma: Double)(x: Double): Double

    

    Cumulative distribution function of a unimodal Gaussian distribution.

    Cumulative distribution function of a unimodal Gaussian distribution.

    Given the mean and standard deviation of a unimodal Gaussian, yields a function for evaluating the CDF of the Gaussian at a point x.

    mu

    Mean of the Gaussian distribution.

    sigma

    Standard deviation of the Gaussian distribution.

    x

    Value for evaluating CDF(x)

    returns

    CDF(x) for the unimodal Gaussian distribution.

15. final def isInstanceOf[T0]: Boolean

    

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16. def meanAndConf(ls: Iterable[Double]): Pair[Double]

    

    Given a list of doubles, returns the mean and 95% confidence interval around the mean assuming normally distributed data.

    Given a list of doubles, returns the mean and 95% confidence interval around the mean assuming normally distributed data.

    ls

    List of doubles

    returns

    (mean, 95% confidence interval)

17. def meanAndConfBS(ls: Seq[Double]): (Double, Pair[Double])

    

    Like meanAndConf but for a bootstrapped data set

    Like meanAndConf but for a bootstrapped data set

    ls

    values

    returns

    (mean, values corresponding to 95% confidence interval)

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

    

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19. final def notify(): Unit

    

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20. final def notifyAll(): Unit

    

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

    

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22. def toString(): String

    

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23. final def wait(): Unit

    

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

    

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

    

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