Ordinary least square regression, orthogonal regression, geometric mean regression and their applications in aerosol science

Journal of Physics: Conference Series

Volumn 78, Issue 1, 2007, Pages

  Leng, Ling ^a   Zhang, Tianyi ^a   Kleinman, Lawrence ^b   Zhu, Wei ^a  

^a STONY BROOK UNIVERSITY   (United States)

^b BROOKHAVEN NATIONAL LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 36048939628     PISSN: 17426588     EISSN: 17426596     Source Type: Conference Proceeding    
DOI: 10.1088/1742-6596/78/1/012084     Document Type: Article

References (9)

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2. Wong M Y 1989 Likelihood estimation of a simple linear regression model when both variables have error Biometrica 76 (1) 141-148
3. Jackson J D and J A Dunlevy 1988 Orthogonal Least Squares and the Interchangeability of Alternative Proxy Variables in the Social Sciences The Statistician 37 (1) 7-14
4. Sprent P and G R Dolby 1980 Query: the geometric mean functional relationship Biometrics 36 (3) 547-550
5. Jolicouer P 1975 Linear regressions in Fishery research: some comments J. Fish. Res. Board Can. 32 (8) 1491-1494
6. Creasy M A 1956 Con_dence limits for the gradient in the linear functional relationship J. R. Statist. Soc. Ser. B 18 65-69
7. Barker F, Y C Soh and R J Evans 1988 Properties of the geometric mean functional relationship Biometrics 44 (1) 279-281
8. Kleinman L, et al 2007 Time Evolution of Aerosol Composition over the Mexico City Plateau (manuscript in preperation for Atmospheric Chemistry and Physics Discussions)
9. McGraw R and R Zhang 2007 Multivariate analysis of homogeneous nucleation rate measurements: I. Nucleation in the p-toluic acid/sulfuric acid/water system. (manuscript)