SSJ
V. 2.2.

umontreal.iro.lecuyer.gof
Class FBar

java.lang.Object
  extended by umontreal.iro.lecuyer.gof.FBar

public class FBar
extends Object

WARNING: All methods in this class are deprecated, except the method scan. They now call the method barF of the appropriate class in package probdist, which use better approximations than the ones that were previously used in this class.

This class is similar to FDist, except that it provides static methods to compute or approximate the complementary distribution function of X, which we define as bar(F)(x) = P[X >= x], instead of F(x) = P[X <= x]. Note that with our definition of bar(F), one has bar(F)(x) = 1 - F(x) for continuous distributions and bar(F)(x) = 1 - F(x - 1) for discrete distributions over the integers. This is non-standard but we find it convenient.

For more details about the specific distributions, see the class FDist. When F(x) is very close to 1, these methods generally provide much more precise values of bar(F)(x) than using 1 - F(x) where F(x) is computed by a method from FDist.


Method Summary
static double andersonDarling(int n, double x)
          Deprecated. 
static double cramerVonMises(int n, double x)
          Deprecated. 
static double kolmogorovSmirnov(int n, double x)
          Deprecated. 
static double kolmogorovSmirnovPlus(int n, double x)
          Deprecated. 
static double scan(int n, double d, int m)
          Return P[SN(d ) >= m], where SN(d ) is the scan statistic.
static double watsonG(int n, double x)
          Deprecated. 
static double watsonU(int n, double x)
          Deprecated. 
 
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Method Detail

kolmogorovSmirnov

@Deprecated
public static double kolmogorovSmirnov(int n,
                                                  double x)
Deprecated. 

Use KolmogorovSmirnovDistQuick.barF(n, x) instead. Returns P[Dn > x], where Dn is the Kolmogorov-Smirnov statistic.

Parameters:
n - sample size
x - Kolmogorov-Smirnov statistic
Returns:
the complementary distribution function of the statistic evaluated at x

kolmogorovSmirnovPlus

@Deprecated
public static double kolmogorovSmirnovPlus(int n,
                                                      double x)
Deprecated. 

Use KolmogorovSmirnovPlusDist.barF(n, x) instead. Returns P[Dn+ > x], where Dn+ is the Kolmogorov-Smirnov+ statistic.

Parameters:
n - sample size
x - Kolmogorov-Smirnov+ statistic
Returns:
the complementary distribution function of the statistic evaluated at x

cramerVonMises

@Deprecated
public static double cramerVonMises(int n,
                                               double x)
Deprecated. 

Use CramerVonMisesDist.barF(n, x) instead. Returns P[Wn2 > x], where Wn2 is the Cramér-von Mises statistic.

Parameters:
n - sample size
x - Cramér-von Mises statistic
Returns:
the complementary distribution function of the statistic evaluated at x

watsonU

@Deprecated
public static double watsonU(int n,
                                        double x)
Deprecated. 

Use WatsonUDist.barF(n, x) instead. Returns P[Un2 > x], where Un2 is the Watson U statistic.

Parameters:
n - sample size
x - Watson Un2 statistic
Returns:
the complementary distribution function of the statistic evaluated at x

watsonG

@Deprecated
public static double watsonG(int n,
                                        double x)
Deprecated. 

Use WatsonGDist.barF(n, x) instead. Returns P[Gn > x], where Gn is the Watson G statistic.

Parameters:
n - sample size
x - Watson G statistic
Returns:
the complementary distribution function of the statistic evaluated at x

andersonDarling

@Deprecated
public static double andersonDarling(int n,
                                                double x)
Deprecated. 

Use AndersonDarlingDistQuick.barF(n, x) instead. Returns P[An2 > x], where An2 is the Anderson-Darling statistic.

Parameters:
n - sample size
x - Anderson-Darling statistic
Returns:
the complementary distribution function of the statistic evaluated at x

scan

public static double scan(int n,
                          double d,
                          int m)
Return P[SN(d ) >= m], where SN(d ) is the scan statistic. It is defined as

SN(d )= sup0 <= y <= 1-dη[yy + d],

where d is a constant in (0, 1), η[yy + d] is the number of observations falling inside the interval [y, y + d], from a sample of N i.i.d. U(0, 1) random variables. The approximation returned by this function is generally good when it is close to 0, but is not very reliable when it exceeds, say, 0.4. Restrictions: N >= 2 and d <= 1/2.

Parameters:
n - sample size ( >= 2)
d - length of the test interval (∈(0, 1))
m - scan statistic
Returns:
the complementary distribution function of the statistic evaluated at m

SSJ
V. 2.2.

To submit a bug or ask questions, send an e-mail to Pierre L'Ecuyer.