Počet záznamů: 1
Nonparametric Estimation of Information-Based Measures of Statistical Dispersion
- 1.0378876 - FGÚ 2013 RIV CH eng J - Článek v odborném periodiku
Košťál, Lubomír - Pokora, Ondřej
Nonparametric Estimation of Information-Based Measures of Statistical Dispersion.
Entropy. Roč. 14, č. 7 (2012), s. 1221-1233. E-ISSN 1099-4300
Grant CEP: GA ČR(CZ) GAP103/11/0282; GA ČR(CZ) GBP304/12/G069; GA ČR(CZ) GPP103/12/P558
Institucionální podpora: RVO:67985823
Klíčová slova: statistical dispersion * entropy * Fisher information * nonparametric density estimation * neuronal activity
Kód oboru RIV: FH - Neurologie, neurochirurgie, neurovědy
Impakt faktor: 1.347, rok: 2012
The maximum penalized likelihood estimation of the probability density function proposed by Good and Gaskins is applied and a complete methodology of how to estimate the dispersion measures of positive random variables with a single algorithm is presented. The approach is illustrated on three standard statistical models describing neuronal activity
Trvalý link: http://hdl.handle.net/11104/0210209
Počet záznamů: 1