URI: http://www.uncertml.org/distributions/cauchy CauchyDistribution Cauchy-Lorenz distribution, Lorenz distribution, Breit-Wigner distribution A random variable $$x$$ follows a Cauchy distribution if the probability density function (pdf) is of the form shown below. The Cauchy distribution is equivalent to a Student-t distribution with 1 degree of freedom. It is widely used in physics, optics and astronomy. $$\theta$$ (location) a real,$$\gamma$$ (scale) a positive real. $$x \in \mathcal{R}$$ $$f(x; \theta, \gamma) = \frac{1}{\pi \gamma} \left[1 + \left( \frac{x - \theta}{\gamma} \right)^2 \right]^{-1}$$ http://en.wikipedia.org/wiki/Cauchy_distribution continuous variables, distribution http://mathworld.wolfram.com/CauchyDistribution.html http://en.wikipedia.org/wiki/Cauchy_distribution    3.14 3.14 3.14 6.28 9.42 3.14 6.28 9.42  // Single value {"CauchyDistribution":{"location":[3.14],"scale":[3.14]}} // Multiple values {"CauchyDistribution":{"location":[3.14,6.28,9.42],"scale":[3.14,6.28,9.42]}}  // Single value declaration CauchyDistribution cd = new CauchyDistribution(3.14, 3.14); // Multiple value declaration CauchyDistribution cd = new CauchyDistribution(new double[] {3.14, 6.28, 9.42}, new double[] {3.14, 6.28, 9.42}); // Parsing from an XML file XMLParser xml = new XMLParser(); CauchyDistribution cd = (CauchyDistribution)xml.parse(new File("cauchy-distribution.xml")); // Parsing from a JSON file JSONParser json = new JSONParser(); CauchyDistribution cd = (CauchyDistribution)json.parse(new File("cauchy-distribution.json")); // Encoding to an XML file XMLEncoder xEncoder = new XMLEncoder(); xEncoder.encode(cd, new File("cauchy-distribution.xml")); // Encoding to a JSON file JSONEncoder jEncoder = new JSONEncoder(); jEncoder.encode(cd, new File("cauchy-distribution.json"));