SSJ
V. 2.6.

umontreal.iro.lecuyer.probdistmulti
Class ContinuousDistribution2Dim

java.lang.Object
  extended by umontreal.iro.lecuyer.probdistmulti.ContinuousDistributionMulti
      extended by umontreal.iro.lecuyer.probdistmulti.ContinuousDistribution2Dim
Direct Known Subclasses:
BiNormalDist, BiStudentDist

public abstract class ContinuousDistribution2Dim
extends ContinuousDistributionMulti

Classes implementing 2-dimensional continuous distributions should inherit from this class. Such distributions are characterized by a density function f (x, y); thus the signature of a density method is supplied here. This class also provides a default implementation of bar(F)(x, y), the upper CDF. The inverse function F-1(u) represents a curve y = h(x) of constant u and it is not implemented.


Field Summary
 int decPrec
          Defines the target number of decimals of accuracy when approximating a distribution function, but there is no guarantee that this target is always attained.
 
Constructor Summary
ContinuousDistribution2Dim()
           
 
Method Summary
 double barF(double x, double y)
          .
abstract  double cdf(double x, double y)
          .
 double cdf(double a1, double a2, double b1, double b2)
          .
 double density(double[] x)
          Simply calls density (x[0], x[1]).
abstract  double density(double x, double y)
          Returns f (x, y), the density of (X, Y) evaluated at (x, y).
 
Methods inherited from class umontreal.iro.lecuyer.probdistmulti.ContinuousDistributionMulti
getCorrelation, getCovariance, getDimension, getMean
 
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Field Detail

decPrec

public int decPrec
Defines the target number of decimals of accuracy when approximating a distribution function, but there is no guarantee that this target is always attained.

Constructor Detail

ContinuousDistribution2Dim

public ContinuousDistribution2Dim()
Method Detail

density

public abstract double density(double x,
                               double y)
Returns f (x, y), the density of (X, Y) evaluated at (x, y).

Parameters:
x - value x at which the density is evaluated
y - value y at which the density is evaluated
Returns:
density function evaluated at (x, y)

density

public double density(double[] x)
Simply calls density (x[0], x[1]).

Specified by:
density in class ContinuousDistributionMulti
Parameters:
x - point (x[0], x[1]) at which the density is evaluated
Returns:
density function evaluated at (x[0], x[1])

cdf

public abstract double cdf(double x,
                           double y)
. Computes the distribution function F(x, y):

F(x, y) = P[X <= x, Y <= y] = ∫-∞xds-∞ydt f (s, t).

Parameters:
x - value x at which the distribution function is evaluated
y - value y at which the distribution function is evaluated
Returns:
distribution function evaluated at (x, y)

barF

public double barF(double x,
                   double y)
. Computes the upper cumulative distribution function bar(F)(x, y):

bar(F)(x, y) = P[X >= x, Y >= y] = ∫xdsydt f (s, t).

Parameters:
x - value x at which the upper distribution is evaluated
y - value y at which the upper distribution is evaluated
Returns:
upper distribution function evaluated at (x, y)

cdf

public double cdf(double a1,
                  double a2,
                  double b1,
                  double b2)
. Computes the cumulative probability in the square region

P[a1 <= X <= b1a2 <= Y <= b2] = ∫a1b1dxa2b2dy f (x, y).

Parameters:
a1 - x lower limit of the square
a2 - y lower limit of the square
b1 - x upper limit of the square
b2 - y upper limit of the square
Returns:
the cumulative probability in the square region

SSJ
V. 2.6.

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