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ox.gavin.experiments

ConfidenceIntervals

object ConfidenceIntervals

Object to calculate mean and confidence interval, given an array of data.

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  1. final def !=(arg0: Any): Boolean
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  4. def apply(xs: Array[Double], ys: Array[Double], alpha: Double): (Double, Double, Double)

    Find mean and confidence intervals with significance alpha for the ratio between the observations ys and xs.

    Find mean and confidence intervals with significance alpha for the ratio between the observations ys and xs. I.e. returns a triple (m,s0,s1) such that m is the ratio of the means of ys and xs, and in a proportion 1-alpha of cases, the mean of the expectations of the underlying distribution lies in the interval [m-s0, m+s1]. This assumes that the underlying distributions are normally distributed.

  5. def apply(xs: Array[Double], alpha: Double): (Double, Double)

    Find mean and confidence intervals with significance alpha for the observations xs.

    Find mean and confidence intervals with significance alpha for the observations xs. I.e. returns a pair (m, s) such that in a proportion 1-alpha of cases, the mean of the underlying distribution lies in the interval [m-s, m+s].

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  14. def meanSD(xs: Array[Double]): (Double, Double)

    Find mean and standard deviation of the observations xs.

  15. def meanVar(xs: Array[Double]): (Double, Double)

    Find mean and variance of the observations xs.

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  24. object Gaussian

    Gaussian distribution

  25. object StudentT

    Student T distribution

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