JUCS - Journal of Universal Computer Science 12(9): 1332-1344, doi: 10.3217/jucs-012-09-1332
Parameter Estimation of the Cauchy Distribution in Information Theory Approach
expand article infoFerenc Nagy‡
‡ University of Miskolc, Hungary

Corresponding author: Ferenc Nagy ( matnf@gold.uni-miskolc.hu )

© Ferenc Nagy.
This article is freely available under the J.UCS Open Content License.
Citation: Nagy F (2006) Parameter Estimation of the Cauchy Distribution in Information Theory Approach. JUCS - Journal of Universal Computer Science 12(9): 1332-1344. https://doi.org/10.3217/jucs-012-09-1332
Open Access
Abstract
As we know the Cauchy distribution plays an important role in Probability Theory and Statistics. In this paper, we investigate the estimation of the location and the scale parameter. Both the one-dimensional problem and the multidimensional problem are studied for large sample. In the one-dimensional case, we give two algorithms for the estimation. The first one is an iterative method for which we prove the convergence and we show that the rate of convergence is geometric. The second algorithm provides an exact solution to the problem. In the multidimensional case, we give an algorithm analogous to the one-dimensional case. Computer experiments show that the rate of convergence is similar to the one-dimensional iterative algorithm.
Keywords
parameter estimation, discrimination information, inaccuracy, Cauchy distribution