Fisher Information Matrix of General Stable Distributions Close to the Normal Distribution
Muneya Matsui
Abstract
We investigate behavior of the Fisher information matrix of general stable distributions. DuMouchel (1975, 1983) proved that the Fisher information of characteristic exponent αdiverges to infinity as αapproaches 2. Nagaev and Shkol'nik (1988) made more detailed analysis and derived asymptotic behavior of the Fisher information matrix of αdiverging to infinity as αapproaches 2 in the symmetric case. Extending their work in this paper we have obtained behavior of the Fisher information matrix of general stable distributions as αapproaches 2 by detailed study of behavior of the corresponding density and its score functions. We clarify the limiting values of the 4*4 Fisher Information matrix with respect to the location μ, the scale σ, the characteristic exponent αand the skewness parameter β.
Create a lesson
Related papers
On diagonal sections of Markov products of copulas
Roman Drnovšek, Damjana Kokol Bukovšek, Nik Stopar
Beyond Discrepancy: Oracle Drift in Nonstationary Weighted Risk Minimization
Tobias Brock, Thomas Nagler
Estimating ratio of variance components in a balanced one-way random effect model
Somnath Mondal, Lakshmi Kanta Patra
Brown's loss function and estimation of the scale parameter and the entropy in scale mixture models with unknown location
Stavros Kourouklis
Finite-Sample Bounds for Fréchet Means of Dependent Data in Metric Spaces with Curvature Bounded Above
Zoraida F. Rico, Christof Schötz
On Eigenvector Statistics of Large-Dimensional Sample Covariance Matrices with Applications
Weiming Li, Zeng Li, Qinwen Wang