Examples of org.jquantlib.math.distributions.GammaFunction.logValue()

Package org.jquantlib.math.distributions

Class org.jquantlib.math.distributions.GammaFunction

Examples of org.jquantlib.math.distributions.GammaFunction.logValue()

org.jquantlib.math.distributions.GammaFunction.logValue()
Computes the log of the Gamma. @param x @return -temp+Math.log(2.5066282746310005*ser/x)

            return 1.0;
        else
            if (x<0.0 || x>1.0)
                throw new ArithmeticException("x must be in [0,1]");


        final double result = Math.exp(gf.logValue(a+b) - gf.logValue(a) - gf.logValue(b) + a*Math.log(x) + b*Math.log(1.0-x));


        if (x < (a+1.0)/(a+b+2.0))
            return result * betaContinuedFraction(a, b, x, accuracy, maxIteration)/a;
        else
            return 1.0 - result * betaContinuedFraction(b, a, 1.0-x, accuracy, maxIteration)/b;

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            return 1.0;
        else
            if (x<0.0 || x>1.0)
                throw new ArithmeticException("x must be in [0,1]");


        final double result = Math.exp(gf.logValue(a+b) - gf.logValue(a) - gf.logValue(b) + a*Math.log(x) + b*Math.log(1.0-x));


        if (x < (a+1.0)/(a+b+2.0))
            return result * betaContinuedFraction(a, b, x, accuracy, maxIteration)/a;
        else
            return 1.0 - result * betaContinuedFraction(b, a, 1.0-x, accuracy, maxIteration)/b;

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            return 1.0;
        else
            if (x<0.0 || x>1.0)
                throw new ArithmeticException("x must be in [0,1]");


        final double result = Math.exp(gf.logValue(a+b) - gf.logValue(a) - gf.logValue(b) + a*Math.log(x) + b*Math.log(1.0-x));


        if (x < (a+1.0)/(a+b+2.0))
            return result * betaContinuedFraction(a, b, x, accuracy, maxIteration)/a;
        else
            return 1.0 - result * betaContinuedFraction(b, a, 1.0-x, accuracy, maxIteration)/b;

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            return 1.0 - result * betaContinuedFraction(b, a, 1.0-x, accuracy, maxIteration)/b;
    }


    static double betaFunction(final double z, final double w) {
        final GammaFunction gf = new GammaFunction();
        return Math.exp(gf.logValue(z)+gf.logValue(w)-gf.logValue(z+w));
    }
}

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            return 1.0 - result * betaContinuedFraction(b, a, 1.0-x, accuracy, maxIteration)/b;
    }


    static double betaFunction(final double z, final double w) {
        final GammaFunction gf = new GammaFunction();
        return Math.exp(gf.logValue(z)+gf.logValue(w)-gf.logValue(z+w));
    }
}

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            return 1.0 - result * betaContinuedFraction(b, a, 1.0-x, accuracy, maxIteration)/b;
    }


    static double betaFunction(final double z, final double w) {
        final GammaFunction gf = new GammaFunction();
        return Math.exp(gf.logValue(z)+gf.logValue(w)-gf.logValue(z+w));
    }
}

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            return 1.0;
        else
            if (x<0.0 || x>1.0)
                throw new ArithmeticException("x must be in [0,1]");


        final double result = Math.exp(gf.logValue(a+b) - gf.logValue(a) - gf.logValue(b) + a*Math.log(x) + b*Math.log(1.0-x));


        if (x < (a+1.0)/(a+b+2.0))
            return result * betaContinuedFraction(a, b, x, accuracy, maxIteration)/a;
        else
            return 1.0 - result * betaContinuedFraction(b, a, 1.0-x, accuracy, maxIteration)/b;

View Full Code Here

            return 1.0;
        else
            if (x<0.0 || x>1.0)
                throw new ArithmeticException("x must be in [0,1]");


        final double result = Math.exp(gf.logValue(a+b) - gf.logValue(a) - gf.logValue(b) + a*Math.log(x) + b*Math.log(1.0-x));


        if (x < (a+1.0)/(a+b+2.0))
            return result * betaContinuedFraction(a, b, x, accuracy, maxIteration)/a;
        else
            return 1.0 - result * betaContinuedFraction(b, a, 1.0-x, accuracy, maxIteration)/b;

View Full Code Here

            return 1.0;
        else
            if (x<0.0 || x>1.0)
                throw new ArithmeticException("x must be in [0,1]");


        final double result = Math.exp(gf.logValue(a+b) - gf.logValue(a) - gf.logValue(b) + a*Math.log(x) + b*Math.log(1.0-x));


        if (x < (a+1.0)/(a+b+2.0))
            return result * betaContinuedFraction(a, b, x, accuracy, maxIteration)/a;
        else
            return 1.0 - result * betaContinuedFraction(b, a, 1.0-x, accuracy, maxIteration)/b;

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            return 1.0 - result * betaContinuedFraction(b, a, 1.0-x, accuracy, maxIteration)/b;
    }


    static double betaFunction(final double z, final double w) {
        final GammaFunction gf = new GammaFunction();
        return Math.exp(gf.logValue(z)+gf.logValue(w)-gf.logValue(z+w));
    }
}

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