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java.lang.Objectumontreal.iro.lecuyer.probdistmulti.ContinuousDistributionMulti
umontreal.iro.lecuyer.probdistmulti.ContinuousDistribution2Dim
public abstract class ContinuousDistribution2Dim
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 | |
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ContinuousDistribution2Dim()
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| Method Summary | |
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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 |
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getCorrelation, getCovariance, getDimension, getMean |
| Methods inherited from class java.lang.Object |
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equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
| Field Detail |
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public int decPrec
| Constructor Detail |
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public ContinuousDistribution2Dim()
| Method Detail |
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public abstract double density(double x,
double y)
x - value x at which the density is evaluatedy - value y at which the density is evaluated
public double density(double[] x)
density in class ContinuousDistributionMultix - point
(x[0], x[1]) at which the density is evaluated
public abstract double cdf(double x,
double y)
x - value x at which the distribution function is evaluatedy - value y at which the distribution function is evaluated
public double barF(double x,
double y)
x - value x at which the upper distribution is evaluatedy - value y at which the upper distribution is evaluated
public double cdf(double a1,
double a2,
double b1,
double b2)
a1 - x lower limit of the squarea2 - y lower limit of the squareb1 - x upper limit of the squareb2 - y upper limit of the square
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SSJ V. 1.2.5. |
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