Pregled bibliografske jedinice broj: 1183289
Numerical Algorithms for Estimating Probability Density Function Based on the Maximum Entropy Principle and Fup Basis Functions
Numerical Algorithms for Estimating Probability Density Function Based on the Maximum Entropy Principle and Fup Basis Functions // Entropy (Basel. Online), 23 (2021), 12; 1559, 19 doi:10.3390/e23121559 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 1183289 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Numerical Algorithms for Estimating Probability
Density Function Based on the Maximum Entropy
Principle and Fup Basis Functions
Autori
Brajčić Kurbaša, Nives ; Gotovac, Blaž ; Kozulić, Vedrana ; Gotovac, Hrvoje
Izvornik
Entropy (Basel. Online) (1099-4300) 23
(2021), 12;
1559, 19
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
maximum entropy ; Shannon entropy ; Fup basis functions ; probability density function
Sažetak
Estimation of the probability density function from the statistical power moments presents a challenging nonlinear numerical problem posed by unbalanced nonlinearities, numerical instability and a lack of convergence, especially for larger numbers of moments. Despite many numerical improvements over the past two decades, the classical moment problem of maximum entropy (MaxEnt) is still a very demanding numerical and statistical task. Among others, it was presented how Fup basis functions with compact support can significantly improve the convergence properties of the mentioned nonlinear algorithm, but still, there is a lot of obstacles to an efficient pdf solution in different applied examples. Therefore, besides the mentioned classical nonlinear Algorithm 1, in this paper, we present a linear approximation of the MaxEnt moment problem as Algorithm 2 using exponential Fup basis functions. Algorithm 2 solves the linear problem, satisfying only the proposed moments, using an optimal exponential tension parameter that maximizes Shannon entropy. Algorithm 2 is very efficient for larger numbers of moments and especially for skewed pdfs. Since both Algorithms have pros and cons, a hybrid strategy is proposed to combine their best approximation properties.
Izvorni jezik
Engleski
POVEZANOST RADA
Projekti:
EK-EFRR-KK.01.1.1.02.0027 - Implementacijom suvremene znanstvenoistraživačke infrastrukture na FGAG Split do pametne specijalizacije u zelenoj i energetski učinkovitoj gradnji (Jajac, Nikša, EK - KK.01.1.1.02) ( CroRIS)
Ustanove:
Fakultet građevinarstva, arhitekture i geodezije, Split
Profili:
Blaž Gotovac
(autor)
Nives Brajčić Kurbaša
(autor)
Hrvoje Gotovac
(autor)
Vedrana Kozulić
(autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus