| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0358733 |
| utime |
20240103195104.1 |
| mtime |
20121107235959.9 |
| title
(primary) (eng) |
Elliptical Stable Distributions |
| specification |
|
| serial |
| ARLID |
cav_un_epca*0349667 |
| ISBN |
978-80-7394-218-2 |
| title
|
Mathematical Methods in Economics 2010 |
| publisher |
| place |
Ceske Budejovice |
| name |
University of South Bohemia |
| year |
2010 |
|
| editor |
|
| editor |
| name1 |
Friebelova |
| name2 |
Jana |
|
|
| keyword |
Stable Distribution |
| keyword |
Elliptical stable distributions |
| keyword |
Maximum Likelihood Projections Estimators |
| author
(primary) |
| ARLID |
cav_un_auth*0271480 |
| name1 |
Omelchenko |
| name2 |
Vadym |
| full_dept (cz) |
Ekonometrie |
| full_dept (eng) |
Department of Econometrics |
| department (cz) |
E |
| department (eng) |
E |
| institution |
UTIA-B |
| full_dept |
Department of Econometrics |
| garant |
G |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| project_id |
GD402/09/H045 |
| agency |
GA ČR |
| ARLID |
cav_un_auth*0253998 |
|
| research |
CEZ:AV0Z10750506 |
| abstract
(eng) |
The elliptical stable distributions represent a symmetric subfamily of the stable distributions. Their advantage contrary to the general stable distributions consists in their easy-to-use property and the highest resemblance to the normal distribution. They enable an easy representation of the dependence structure of the margins by means of a matrix Q the same as in case of the normal distribution. In general, the dependence structure between margins is given in form of a spectral measure which can be even continuous. The computations and approximations require so much time that it just the fact that many practitioners avoid using general stable distributions. The general stable distributions possess so many additional properties that they barely take after the multivariate normal distribution. But the multi-variate elliptical stable distributions can be easily simulated and the estimation of their parameters can be obtained by methods whose preciseness is almost the same as the one of the maximum likelihood methodology. |
| action |
| ARLID |
cav_un_auth*0263925 |
| name |
Mathematical Methods in Economics 2010 |
| place |
České Budějovice |
| dates |
08.09.2010-10.09.2010 |
| country |
CZ |
|
| reportyear |
2013 |
| RIV |
AH |
| num_of_auth |
1 |
| permalink |
http://hdl.handle.net/11104/0196682 |
| arlyear |
2010 |
| mrcbU63 |
cav_un_epca*0349667 Mathematical Methods in Economics 2010 978-80-7394-218-2 Mathematical Methods in Economics 2010 Ceske Budejovice University of South Bohemia 2010 |
| mrcbU67 |
Houda Michal 340 |
| mrcbU67 |
Friebelova Jana 340 |
|