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Volumn 27, Issue 5, 2003, Pages 701-714

The SROV program for data analysis and regression model identification

Author keywords

Colinearity; Noise; Non influential variable; Precision; Stepwise regression

Indexed keywords

DATA REDUCTION; FUNCTIONS; MATHEMATICAL MODELS; NONLINEAR SYSTEMS;

EID: 0037447825     PISSN: 00981354     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0098-1354(02)00260-0     Document Type: Article
Times cited : (42)

References (17)
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  • 3
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    • Regression diagnostic using an orthogonalized variable based stepwise regression procedure
    • Brauner, N., & Shacham, M. (1999). Regression diagnostic using an orthogonalized variable based stepwise regression procedure. Computers and Chemical Engineering 23 Supplement, S327-S331.
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    • Brauner, N.1    Shacham, M.2
  • 4
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    • A software toolbox for data analysis and regression, considering data precision and numerical error propagation
    • The Hague, 26-29 May 2002
    • Brauner, N., & Shacham, M. (2002). A software toolbox for data analysis and regression, considering data precision and numerical error propagation. In: Proceedings of the ESCAPE 12 conference, The Hague, 26-29 May 2002.
    • (2002) Proceedings of the ESCAPE 12 Conference
    • Brauner, N.1    Shacham, M.2
  • 7
    • 0020998928 scopus 로고
    • A misuse of ridge regression in the calibration of near infrared reflectance instrument
    • Fearn, T. (1983). A misuse of ridge regression in the calibration of near infrared reflectance instrument. Applied Statistics 32 (10), 73-79.
    • (1983) Applied Statistics , vol.32 , Issue.10 , pp. 73-79
    • Fearn, T.1
  • 12
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    • A new method for optimizing the structure of thermodynamic correlation equations
    • Setzmann, U., & Wagner, W. (1989). A new method for optimizing the structure of thermodynamic correlation equations. International Journal of Thermophysics 10 (6), 1103.
    • (1989) International Journal of Thermophysics , vol.10 , Issue.6 , pp. 1103
    • Setzmann, U.1    Wagner, W.2
  • 13
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    • Minimizing the effects of colinearity in polynomial regression
    • Shacham, M., & Brauner, N. (1997). Minimizing the effects of colinearity in polynomial regression. Industrial & Engineering Chemistry Research 36 (10), 4405-4412.
    • (1997) Industrial & Engineering Chemistry Research , vol.36 , Issue.10 , pp. 4405-4412
    • Shacham, M.1    Brauner, N.2
  • 14
    • 0033378914 scopus 로고    scopus 로고
    • Considering precision of experimental data in construction of optimal regression models
    • Shacham, M., & Brauner, N. (1999a). Considering precision of experimental data in construction of optimal regression models. Chemical Engineering and Processing 38, 477-486.
    • (1999) Chemical Engineering and Processing , vol.38 , pp. 477-486
    • Shacham, M.1    Brauner, N.2
  • 16
    • 84972517124 scopus 로고
    • Colinearity and least squares regression
    • Stewart, G. W. (1987). Colinearity and least squares regression. Statistical Sciences 2 (1), 68-100.
    • (1987) Statistical Sciences , vol.2 , Issue.1 , pp. 68-100
    • Stewart, G.W.1
  • 17
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    • New vapor pressure measurements for argon and nitrogen and a new method for establishing rational vapor pressure equations
    • Wagner, W. (1973). New vapor pressure measurements for argon and nitrogen and a new method for establishing rational vapor pressure equations. Cryogenics 13, 470-482.
    • (1973) Cryogenics , vol.13 , pp. 470-482
    • Wagner, W.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.