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

Linear Supertypes
AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. MethodOfMoments
  2. AnyRef
  3. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Type Members

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

    Standard functional form for parameter estimating functions

Value Members

  1. final def !=(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0
    Definition Classes
    Any
  5. 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

  6. 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

  7. def clone(): AnyRef
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  8. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  9. def equals(arg0: Any): Boolean
    Definition Classes
    AnyRef → Any
  10. 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

  11. def finalize(): Unit
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  12. 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

  13. 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

  14. final def getClass(): Class[_]
    Definition Classes
    AnyRef → Any
  15. def hashCode(): Int
    Definition Classes
    AnyRef → Any
  16. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  17. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  18. 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

  19. final def notify(): Unit
    Definition Classes
    AnyRef
  20. final def notifyAll(): Unit
    Definition Classes
    AnyRef
  21. 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

  22. 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

  23. final def synchronized[T0](arg0: ⇒ T0): T0
    Definition Classes
    AnyRef
  24. def toString(): String
    Definition Classes
    AnyRef → Any
  25. 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

  26. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  27. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  28. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from AnyRef

Inherited from Any

Ungrouped