Optimal transformations for categorical autoregressive time series

Statistica Neerlandica

Volumn 51, Issue 1, 1997, Pages 90-106

  Van Buuren, S ^a  

^a TNO   (Netherlands)

Author keywords

Autoregressive model; Canonical correlation; Intervention analysis; Majorization; Nonlinear transformations; Predictable components; Qualitative data; Quantification; Smoothing

Indexed keywords

EID: 0031537766     PISSN: 00390402     EISSN: None     Source Type: Journal    
DOI: 10.1111/1467-9574.00039     Document Type: Article

References (34)

1. ANSLEY, C. F., W. A. SPIVEY and W. J. WROBLESKI (1977), A class of transformations for Box-Jenkins seasonal models, Applied Statistics 26, 173-178.
2. BISHOP, Y. M. M., S. E. FIENBERG and P. W. HOLLAND (1975), Discrete multivariate analysis: theory and practice, MIT Press, Cambridge, MA.
3. Box, G. E. P. and G. W. JENKINS (1976), Time series analysis: forecasting and control, Revised edition, Holden-Day, San Francisco.
4. Box, G. E. P. and G. C. TIAO (1977), A canonical analysis of multiple time series, Biometrika 64, 355-365.
5. VAN BUUREN, S. (1990), Optimal scaling of time series, Dissertation, University of Utrecht. DSWO Press, Leiden.
6. VAN BUUREN, S. (1992), Predictable linear combinations from categorical time series, Statistica Applicata: Italian Journal of Applied Statistics 4, 743-751.
7. VAN BUUREN, S. (1996), Fitting ARMA time series by structural equation models, Psychometrika, in press.
8. VAN BUUREN, S. and J. DE LEEUW (1992), Equality constraints in multiple correspondence analysis, Multivariate Behavioral Research 27, 567-583.
9. DEVILLE, J-C. and G. SAPORTA (1983). Correspondence analysis with an extension towards nominal time series. Journal of Econometrics 22, 169-189.
10. EFRON, B. and R. J. TIBSHIRANI (1993). An introduction to the bootstrap, Chapman and Hall, London.
11. FAHRMEIR, L. (1992), State space modeling and conditional mode estimation for categorical time series, in: D. R. Brillinger et al. (eds.), New directions in time series analysis, part I (pp. 87-109), Springer, Berlin.
12. GHADDAR, D. K. and H. TONG (1981), Data transformation and self-exciting threshold autoregression, Applied Statistics 30, 238-248.
13. GIFI, A. (1990), Nonlinear multivariate analysis, Wiley, Chichester.
14. GLASS, G. V., V. L. WILLSON and J. M. GOTTMAN (1975), Design and analysis of time series experiments, Colorado Associated University Press, Boulder, Colorado.
15. GOODALL, C. (1990), A survey of smoothing techniques, in: J. Fox and J. Scott Long (eds.), Modern methods of data analysis. Sage, London, 126-176.
16. GREGSON, R. A. M. (1987), The time-series analysis of self-reported headache sequences, Behaviour Change 4, 6-13.
17. GRUBB, H. (1992), Review of "Optimal scaling of time series" by S. van Buuren, Journal of the Royal Statistical Society, Series A 155, 179-180.
18. HAND, D. J., F. DALY, A. D. LUNN, K. J. MCCONWAY and E. OSTROWSKI (1993), A handbook of small data sets, Chapman and Hall, London.
19. HARVEY, A. C. and C. FERNANDES (1989), Time series models for count of qualitative observations (with discussion), Journal of Business and Economics Statistics 7, 407-422.
20. HINKLEY, D. (1977), On quick choice of power transformation, Applied Statistics 26, 67-69.
21. HJORTH, J. S. U. (1994), Computer intensive statistical methods, Chapman and Hall, London.
22. JACOBS, P. A. and P. A. W. LEWIS (1978), Discrete time series generated by mixtures, I: correlational and runs properties, Journal of the Royal Statistical Society, Series B 40, 94-105.
23. DE LEEUW, J. (1977), Applications of convex analysis to multidimensional scaling, in: J. R. Barra, F. Brodeau, G. Romier and B. van Cutsum (eds.), Recent developments in statistics, North-Holland, Amsterdam, 137-145.
24. DE LEEUW, J. (1988), Multivariate analysis with linearizable regressions, Psychometrika 53, 437-454.
25. DE LEEUW, J., F. W. YOUNG and Y. TAKANE (1976), Additive structure in qualitative data: an alternating least squares method with optimal scaling features, Psychometrika 41, 471-503.
26. DE LEEUW, J. and W. J. HEISER (1980), Multidimensional scaling with restrictions on the configuration, in: P. R. Krishnaiah (ed.), Multivariate analysis V, North-Holland, Amsterdam, 501-522.
27. OWEN, A. (1983), Optimal transformations for autoregressive time series models, Report LCSD013, Stanford University, Dept. of Statistics.
28. PARZEN, E. and H. J. NEWTON (1980), Multiple time series modelling II, In: P. R. Krishnaiah (ed.), Multivariate analysis V, North Holland, Amsterdam, 107-197.
29. RAVEH, A. and C. S. TAPIERO (1980), Periodicity, constancy, heterogeneity and the categories of qualitative time series, Ecology 61, 715-719.
30. VAN RIJCKEVORSEL, J. L. A. (1987), The application of fuzzy coding and horseshoes in multiple correspondence analysis, Dissertation, University of Leiden, DSWO Press, Leiden.
31. SINGH, A. C. and G. LEMAITRE (1987), Categorical auto-regressive models for analysing panel survey data, ASA Proceedings of the Section of Survey Research Methods, 390-394.
32. STOFFER, D. S. (1991), Walsh-Fourier analysis and its statistical applications, Journal of the American Statistical Association 86, 461-479.
33. VELU, R. P., G. C. REINSEL and D. W. WICHERN (1986), Reduced rank regression models for multiple time series, Biometrika 73, 105-118.
34. YOUNG, M. R. (1990), Estimating optimal transformations for correlation and coherence, in: C. Page and R. LePage (eds.), Computing science and statistics: Proceedings of the Symposium on the Interface, Springer, Berlin, 571-575.