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Volumn 39, Issue 9, 2003, Pages 1651-1659

A random least-trimmed-squares identification algorithm

Author keywords

Least squares; Least trimmed squares; Parameter estimation; Random algorithms; System identification

Indexed keywords

ALGORITHMS; COMPUTATIONAL COMPLEXITY; CONVERGENCE OF NUMERICAL METHODS; LEAST SQUARES APPROXIMATIONS; PROBABILITY; RANDOM PROCESSES;

EID: 0041591130     PISSN: 00051098     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0005-1098(03)00193-6     Document Type: Article
Times cited : (27)

References (11)
  • 1
    • 38149147670 scopus 로고
    • The feasible solution algorithm for least trimmed squares regression
    • Hawkins D.M. The feasible solution algorithm for least trimmed squares regression. Computational Statistics & Data Analysis. 17:1994;185-196.
    • (1994) Computational Statistics & Data Analysis , vol.17 , pp. 185-196
    • Hawkins, D.M.1
  • 2
    • 0036489051 scopus 로고    scopus 로고
    • Inconsistency of resampling algorithms for high-breakdown regression estimators and a new algorithm
    • Hawkins D.M., Olive D. Inconsistency of resampling algorithms for high-breakdown regression estimators and a new algorithm. Journal of the American Statistical Association. 97:2002;136-159.
    • (2002) Journal of the American Statistical Association , vol.97 , pp. 136-159
    • Hawkins, D.M.1    Olive, D.2
  • 5
    • 0041891737 scopus 로고
    • Least median of squares, least trimmed squares and S-estimations by means of BMDP3R and BMDPAR
    • Neykov N., Neytchev P. Least median of squares, least trimmed squares and S-estimations by means of BMDP3R and BMDPAR. Computational Statistics Quarterly. 4:1991;281-293.
    • (1991) Computational Statistics Quarterly , vol.4 , pp. 281-293
    • Neykov, N.1    Neytchev, P.2
  • 8
    • 0000526780 scopus 로고
    • Computing the exact least median of squares estimate and stability diagnostics in multiple linear regression
    • Stromberg A. Computing the exact least median of squares estimate and stability diagnostics in multiple linear regression. SIAM Journal on Scientific Computing. 14:1993;1289-1299.
    • (1993) SIAM Journal on Scientific Computing , vol.14 , pp. 1289-1299
    • Stromberg, A.1
  • 9
    • 0000872569 scopus 로고    scopus 로고
    • Probabilistic robustness analysis; explicit bound for the minimum number of samples
    • Tempo R., Bai E., Dabbene F. Probabilistic robustness analysis; explicit bound for the minimum number of samples. Systems & Control Letters. 30:1997;237-242.
    • (1997) Systems & Control Letters , vol.30 , pp. 237-242
    • Tempo, R.1    Bai, E.2    Dabbene, F.3
  • 10
    • 0011468264 scopus 로고
    • Algorithms for and geometrical characterization of solutions in the LMS and the LTS linear regression
    • Tichavsky, P. (1991). Algorithms for and geometrical characterization of solutions in the LMS and the LTS linear regression. Computational Statistics Quarterly, 139-151.
    • (1991) Computational Statistics Quarterly , pp. 139-151
    • Tichavsky, P.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.