umontreal.iro.lecuyer.probdistmulti
Class BiNormalGenzDist
java.lang.Object
umontreal.iro.lecuyer.probdistmulti.ContinuousDistributionMulti
umontreal.iro.lecuyer.probdistmulti.ContinuousDistribution2Dim
umontreal.iro.lecuyer.probdistmulti.BiNormalDist
umontreal.iro.lecuyer.probdistmulti.BiNormalGenzDist
public class BiNormalGenzDist
- extends BiNormalDist
Extends the class BiNormalDist
for the bivariate
normal distribution
using Genz's algorithm as described in.
Constructor Summary |
BiNormalGenzDist(double rho)
Constructs a BiNormalGenzDist object with default parameters
μ1 = μ2 = 0,
σ1 = σ2 = 1 and correlation
ρ = rho. |
BiNormalGenzDist(double mu1,
double sigma1,
double mu2,
double sigma2,
double rho)
Constructs a BiNormalGenzDist object with parameters μ1 = mu1,
μ2 = mu2, σ1 = sigma1, σ2 = sigma2
and ρ = rho. |
Method Summary |
double |
barF(double x,
double y)
. |
static double |
barF(double x,
double y,
double rho)
|
static double |
barF(double mu1,
double sigma1,
double x,
double mu2,
double sigma2,
double y,
double rho)
|
double |
cdf(double x,
double y)
. |
static double |
cdf(double x,
double y,
double rho)
Computes the standard binormal distribution
with the method described in. |
static double |
cdf(double mu1,
double sigma1,
double x,
double mu2,
double sigma2,
double y,
double rho)
|
Methods inherited from class umontreal.iro.lecuyer.probdistmulti.BiNormalDist |
density, density, density, getCorrelation, getCorrelation, getCovariance, getCovariance, getMean, getMean, getMu1, getMu2, getSigma1, getSigma2 |
BiNormalGenzDist
public BiNormalGenzDist(double rho)
- Constructs a BiNormalGenzDist object with default parameters
μ1 = μ2 = 0,
σ1 = σ2 = 1 and correlation
ρ = rho.
BiNormalGenzDist
public BiNormalGenzDist(double mu1,
double sigma1,
double mu2,
double sigma2,
double rho)
- Constructs a BiNormalGenzDist object with parameters μ1 = mu1,
μ2 = mu2, σ1 = sigma1, σ2 = sigma2
and ρ = rho.
cdf
public static double cdf(double x,
double y,
double rho)
- Computes the standard binormal distribution
with the method described in. The code for the cdf
was translated directly from the Matlab code written by Alan Genz
and available from his web page at
http://www.math.wsu.edu/faculty/genz/homepage (the code is copyrighted by Alan Genz
and is included in this package with the kind permission of the author).
The absolute error is expected to be smaller than
0.5⋅10-15.
cdf
public static double cdf(double mu1,
double sigma1,
double x,
double mu2,
double sigma2,
double y,
double rho)
cdf
public double cdf(double x,
double y)
- Description copied from class:
ContinuousDistribution2Dim
- .
Computes the distribution function F(x, y):
F(x, y) = P[X <= x, Y <= y] = ∫-∞xds∫-∞ydt f (s, t).
- Overrides:
cdf
in class BiNormalDist
- Parameters:
x
- value x at which the distribution function is evaluatedy
- value y at which the distribution function is evaluated
- Returns:
- distribution function evaluated at (x, y)
barF
public double barF(double x,
double y)
- Description copied from class:
ContinuousDistribution2Dim
- .
Computes the upper cumulative distribution function
bar(F)(x, y):
bar(F)(x, y) = P[X >= x, Y >= y] = ∫∞xds∫∞ydt f (s, t).
- Overrides:
barF
in class BiNormalDist
- Parameters:
x
- value x at which the upper distribution is evaluatedy
- value y at which the upper distribution is evaluated
- Returns:
- upper distribution function evaluated at (x, y)
barF
public static double barF(double mu1,
double sigma1,
double x,
double mu2,
double sigma2,
double y,
double rho)
barF
public static double barF(double x,
double y,
double rho)
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