object GoodnessOfFit_KS

The GoodnessOfFit_KS object provides methods to approximate the critical values/p-values for the KS Test.

P(D_n < d)

See also

www.jstatsoft.org/article/view/v008i18/kolmo.pdf

sa-ijas.stat.unipd.it/sites/sa-ijas.stat.unipd.it/files/IJAS_3-4_2009_07_Facchinetti.pdf

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

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 clone(): AnyRef
    Attributes
    protected[lang]
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.CloneNotSupportedException]) @native() @HotSpotIntrinsicCandidate()
  6. final def eq(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  7. def equals(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef → Any
  8. final def getClass(): Class[_ <: AnyRef]
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  9. def hashCode(): Int
    Definition Classes
    AnyRef → Any
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  10. final def isInstanceOf[T0]: Boolean
    Definition Classes
    Any
  11. def ksCDF(d: Double, n: Int): Double

    Compute the Cumulative Distribution Function (CDF) for 'P(D_n < d)'.

    Compute the Cumulative Distribution Function (CDF) for 'P(D_n < d)'. It can used for p-values or critical values for the KS test. Translated from C code given in paper below.

    d

    the maximum distance between empirical and theoretical distribution

    n

    the number of data points

    See also

    www.jstatsoft.org/article/view/v008i18/kolmo.pdf

  12. def lilliefors(d: Double, n: Int): Double

    Compute the critical value for the KS Test using the Lilliefors approximation.

    Compute the critical value for the KS Test using the Lilliefors approximation. Caveat: assumes alpha = .05 and is only accurate to two digits.

    d

    the maximum distance between empirical and theoretical distribution

    n

    the number of data points

    See also

    www.utdallas.edu/~herve/Abdi-Lillie2007-pretty.pdf FIX - use a more flexible and accurate approximation.

  13. final def ne(arg0: AnyRef): Boolean
    Definition Classes
    AnyRef
  14. final def notify(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  15. final def notifyAll(): Unit
    Definition Classes
    AnyRef
    Annotations
    @native() @HotSpotIntrinsicCandidate()
  16. final def synchronized[T0](arg0: => T0): T0
    Definition Classes
    AnyRef
  17. def toString(): String
    Definition Classes
    AnyRef → Any
  18. final def wait(arg0: Long, arg1: Int): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])
  19. final def wait(arg0: Long): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException]) @native()
  20. final def wait(): Unit
    Definition Classes
    AnyRef
    Annotations
    @throws(classOf[java.lang.InterruptedException])

Deprecated Value Members

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

Inherited from AnyRef

Inherited from Any

Ungrouped