메뉴 건너뛰기




Volumn 37, Issue 1, 2001, Pages 1-12

Genetic algorithms for the identification of additive and innovation outliers in time series

Author keywords

Autoregressive moving average (ARMA) process; Fitness function; Genetic algorithms; Interpolation; Linear process; Outliers in time series

Indexed keywords

GENETIC ALGORITHMS; MAXIMUM LIKELIHOOD ESTIMATION; TIME SERIES ANALYSIS;

EID: 0035963957     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0167-9473(00)00058-X     Document Type: Article
Times cited : (25)

References (36)
  • 2
    • 0004410294 scopus 로고    scopus 로고
    • Additive and innovational outliers in autoregressive time series: A unified Bayesian approach
    • (1998) Statistica , vol.58 , pp. 395-409
    • Barbieri, M.M.1
  • 4
    • 0030554449 scopus 로고    scopus 로고
    • Relationship between missing data likelihoods and complete data restricted likelihoods for regression time series models: An application to total ozone data
    • (1996) Appl. Statist , vol.45 , pp. 63-72
    • Basu, S.1    Reinsel, G.C.2
  • 32
    • 0000995328 scopus 로고
    • An approximate inverse for the covariance matrix of moving average and autoregressive processes
    • (1975) Ann. Statist , vol.3 , pp. 532-538
    • Shaman, P.1
  • 36
    • 84944452417 scopus 로고
    • Outliers, level shifts and variance changes in time series
    • (1988) J. Forecast , vol.7 , pp. 1-20
    • Tsay, R.S.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.