Title :
Parameter estimation and data analysis for stable distributions
Author_Institution :
Dept. of Math. & Stat., American Univ., Washington, DC, USA
Abstract :
It is now practical to use maximum likelihood estimation to estimate stable parameters and to give large sample confidence regions. Just as important as estimating parameters is assessing whether or not a given sample is stably distributed. Diagnostics for this purpose are demonstrated. Several methods of estimating the spectral measure of a multivariate stable distribution are described, and diagnostics for assessing stability of a multivariate sample are also demonstrated.
Keywords :
maximum likelihood estimation; spectral analysis; statistical analysis; data analysis; diagnostics; large sample confidence regions; maximum likelihood estimation; multivariate stable distribution; parameter estimation; spectral measure; stability; stable distributions; stable parameters; Books; Contracts; Data analysis; Mathematics; Maximum likelihood estimation; Noise measurement; Parameter estimation; Stability; Statistical distributions; Tail;
Conference_Titel :
Signals, Systems & Computers, 1997. Conference Record of the Thirty-First Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
Print_ISBN :
0-8186-8316-3
DOI :
10.1109/ACSSC.1997.680366
