bibtype J - Journal Article
ARLID 0504580
utime 20240103222020.3
mtime 20190516235959.9
SCOPUS 85057061156
WOS 000455518200024
DOI 10.1007/s00500-018-3623-x
title (primary) (eng) Pseudo-exponential distribution and its statistical applications in econophysics
specification
page_count 7 s.
media_type P
serial
ARLID cav_un_epca*0258368
ISSN 1432-7643
title Soft Computing
volume_id 23
volume 1 (2019)
page_num 357-363
publisher
name Springer
keyword Pseudo-operations
keyword Pseudo-exponential distribution
keyword Moment-generating function
keyword Numerical computation
author (primary)
ARLID cav_un_auth*0375106
share 30
name1 Mehri-Dehnavi
name2 H.
country IR
garant K
author
ARLID cav_un_auth*0261431
share 40
name1 Agahi
name2 H.
country IR
author
ARLID cav_un_auth*0101163
full_dept Department of Econometrics
share 30
name1 Mesiar
name2 Radko
institution UTIA-B
full_dept (cz) Ekonometrie
full_dept Department of Econometrics
department (cz) E
department E
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url http://library.utia.cas.cz/separaty/2019/E/mesiar-0504580.pdf
source
url https://link.springer.com/article/10.1007/s00500-018-3623-x
cas_special
abstract (eng) In generalized measure theory, sigma-circle plus-measure is a generalization of the classical measure defined on a pseudo-addition. In this paper, the class of pseudo-exponential distributions based on a class of sigma-circle plus-measure is introduced. Some examples of this class are investigated. Then by two real data sets obtained from the last three decades of oil, and the last two decades of the daily natural gas spot prices, we show that the pseudo-exponential distribution is better fitted than exponential distribution using the AIC and BIC information criteria.
result_subspec WOS
RIV BA
FORD0 10000
FORD1 10100
FORD2 10103
reportyear 2020
num_of_auth 3
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0297076
confidential S
mrcbC86 3+4 Article Computer Science Artificial Intelligence|Computer Science Interdisciplinary Applications
mrcbC91 C
mrcbT16-e COMPUTERSCIENCEARTIFICIALINTELLIGENCE|COMPUTERSCIENCEINTERDISCIPLINARYAPPLICATIONS
mrcbT16-j 0.499
mrcbT16-s 0.705
mrcbT16-B 32.106
mrcbT16-D Q3
mrcbT16-E Q4
arlyear 2019
mrcbU14 85057061156 SCOPUS
mrcbU24 PUBMED
mrcbU34 000455518200024 WOS
mrcbU63 cav_un_epca*0258368 Soft Computing 1432-7643 1433-7479 Roč. 23 č. 1 2019 357 363 Springer