Packages

o

scalation.stat

MethodOfMoments

object MethodOfMoments

The MethodOfMoments object provides methods for estimating parameters for popular probability distributions using the Method of Moments (MOM). The main alternative is to use Maximum Likelihood Estimators (MLE).

See also

www.math.uah.edu/stat/point/Moments.html

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Type Members

  1. type ParamFunction = (VectorD) ⇒ Array[Double]

    Standard functional form for parameter estimating functions

Value Members

  1. def bernoulli(x: VectorD): Array[Double]

    Estimate the parameter 'p' for the Bernoulli distribution.

    Estimate the parameter 'p' for the Bernoulli distribution.

    x

    the statistical data vector

  2. def beta(x: VectorD): Array[Double]

    Estimate the parameters 'a' (alpha) and 'b' (beta) for the Beta distribution.

    Estimate the parameters 'a' (alpha) and 'b' (beta) for the Beta distribution.

    x

    the statistical data vector

  3. def exponential(x: VectorD): Array[Double]

    Estimate the parameter 'mu' for the Exponential distribution.

    Estimate the parameter 'mu' for the Exponential distribution.

    x

    the statistical data vector

  4. def gamma(x: VectorD): Array[Double]

    Estimate the parameters 'a' (alpha) and 'b' (beta) for the Gamma distribution.

    Estimate the parameters 'a' (alpha) and 'b' (beta) for the Gamma distribution.

    x

    the statistical data vector

  5. def geometric(x: VectorD): Array[Double]

    Estimate the parameter 'p' for the Geometric distribution.

    Estimate the parameter 'p' for the Geometric distribution.

    x

    the statistical data vector

  6. def normal(x: VectorD): Array[Double]

    Estimate the parameters 'mu' and 'sigma2' for the Normal distribution.

    Estimate the parameters 'mu' and 'sigma2' for the Normal distribution.

    x

    the statistical data vector

  7. def pareto(x: VectorD): Array[Double]

    Estimate the parameters 'a' and 'b' for the Pareto distribution.

    Estimate the parameters 'a' and 'b' for the Pareto distribution.

    x

    the statistical data vector

  8. def poisson(x: VectorD): Array[Double]

    Estimate the parameter 'mu' for the Poisson distribution.

    Estimate the parameter 'mu' for the Poisson distribution.

    x

    the statistical data vector

  9. def uniform(x: VectorD): Array[Double]

    Estimate the parameters 'a' and 'b' for the Uniform distribution.

    Estimate the parameters 'a' and 'b' for the Uniform distribution.

    x

    the statistical data vector