Searching for structure in measurements of air pollutant concentration

Environmetrics

Volumn 18, Issue 8, 2007, Pages 823-840

  Morlini, Isabella ^a  

^a UNIVERSITY OF MODENA AND REGGIO EMILIA   (Italy)

Author keywords

Cross sectional mean; Functional data; Landmarks; Warping functions

Indexed keywords

AIR QUALITY; ALGORITHM; ATMOSPHERIC MODELING; ATMOSPHERIC POLLUTION; CROSS SECTION; MEASUREMENT METHOD;

EMILIA-ROMAGNA; EURASIA; EUROPE; ITALY; SOUTHERN EUROPE;

EMILIA;

EID: 38049036959     PISSN: 11804009     EISSN: 1099095X     Source Type: Journal    
DOI: 10.1002/env.842     Document Type: Article

References (18)

1. Corbellini A, Morlini I. 2004. Searching for the optimal smoothing before applying Dynamic Time Warping. Proceedings of the XLII Meeting of the Italian Statistical Society, University of Bari: 47-50.
2. Environmental Protection Agency 1999. Guideline for reporting of daily air quality - air quality index (AQI). EPA-454/R-99-010. Office of air quality planning and standards, Research triangle park, NC 27711.
3. Gervini D, Gasser T. 2004. Self-modelling warping functions. Journal of the Royal Statistical Society, Series B 66: 959-971.
4. Gordon AD. 1991. Classification 2nd edition. Chapman and Hall: London.
5. Gordon AD. 1996. Hierarchical classification. In Clustering and Classification. Arabic P, Hubert LJ, De Soete G (eds). World Scientific Publ.: River Edge, NJ.
6. Green PJ, Silverman BW. 1994. Nonparametric Regression and Generalized Linear Models. Chapman & Hall: London.
7. Kneip A, Gasser T. 1992. Statistical Tools to analyze data representing a sample of curves. Annals of Statistics 20(3): 1266-1305
8. Morlini, I. 2004 On the dynamic time warping for computing the dissimilarities between curves. In New Developments in Classification and Data Analysis. Vichi M, et al. (ed.). Springer-Verlag: Berlin: 63-70.
9. Morlini I, Zani S. 2006. Estimation of the structural man of a sample of curves by dynamic time warping. In Data Analysis, Classification and the Forward Search, Zani S, et al. (ed.). Springer-Verlag: Berlin: 39-48.
10. Rabiner L, Juang B. 1993. Fundamentals of Speech Recognition. Prentice Hall: N.J.
11. Ramsav JO, Dalzell C. 1991. Some tools for functional data analysis (with discussion). Journal of the Royal Statistical Society 53: 539-572.
12. Ramsay JO, Li X. 1998. Curve Registration. Journal of the Royal Statistical Society; Series B 60: 351-363.
13. Ramsay JO, Silverman B. 1997. Functional Data Analysis. Springer: New York.
14. Roberts K, Lawrence P, Eisen A, Hoirch M. 1987. Enhancement and dynamic time warping of somatosensory evoked potential components applied to patients with multiple sclerosis. IEEE Transactions on Biomedical Engineering BME 34: 397-405.
15. Sakoe H, Chiba S. 1978. Dynamic programming algorithm optimization for spoken word recognition. IEEE Transactions on Acoustic, Speech and Signal Processing 26: 43-49.
16. Silverman B. 1995. Incorporating parametric effects into functional principal components analysis. Journal of Royal Statistical Society Series B 57: 673-689.
17. Wang K, Gasser T. 1997. Alignment of curves by dynamic time warping. The Annals of Statistics 25(3): 1251-1276.
18. Wang K, Gasser T. 1999. Synchronizing sample curves nonparametrically. The Annals of Statistics 27(2): 439-460.