Pregled bibliografske jedinice broj: 258954
Estimating the width of a uniform distribution when data are measured with additive normal errors with known variance
Estimating the width of a uniform distribution when data are measured with additive normal errors with known variance // Computational Statistics & Data Analysis, 51 (2007), 9; 4731-4741 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 258954 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Estimating the width of a uniform distribution when data are measured with additive normal errors with known variance
Autori
Benšić, Mirta ; Sabo, Kristian
Izvornik
Computational Statistics & Data Analysis (0167-9473) 51
(2007), 9;
4731-4741
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
maximum likelihood estimator; method of moments estimator;
Sažetak
The problem of estimating the width of the symmetric uniform distribution on the line when data are measured with normal additive error is considered. The main purpose is to discuss the efficiency of the maximum likelihood estimator and the moment method estimator. It is shown that the model is regular and that the maximum likelihood estimator is more efficient than the moment method estimator. A sufficient condition is also given for the existence of both estimators.
Izvorni jezik
Engleski
Znanstvena područja
Matematika
POVEZANOST RADA
Projekti:
073-0731674-0841 - Stanična i tkivna diferencijacija tijekom razvoja biljnih organa
235-2352818-1034 - Nelinearni problemi procjene parametara u matematičkim modelima (Jukić, Dragan, MZOS ) ( CroRIS)
235-2352818-1039 - Statistički aspekti problema procjene u nelinearnim parametarskim modelima (Benšić, Mirta, MZOS ) ( CroRIS)
Ustanove:
Sveučilište u Osijeku, Odjel za matematiku
Citiraj ovu publikaciju:
Časopis indeksira:
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus
Uključenost u ostale bibliografske baze podataka::
- The INSPEC Science Abstracts series
- Mathematical Reviews
- ACM Computing Reviews
- CompuMath Citation Index
- Current Index to Statistics
- Engineering Index
- OR/MS
- QCAS
- Research Alert
- Scopus
- Statistical Theory and Method Abstracts
- Zentralblatt MATH