Nonparametric statistics for testing of linearity and serial independence

Journal of Nonparametric Statistics

Volumn 6, Issue 2-3, 1996, Pages 223-251

  Hjellvik, Vidar ^a   Tjøstheim, Dag ^a  

^a UNIVERSITY OF BERGEN   (Norway)

Author keywords

Conditional mean; Kernel method; Linearity; Serial independence

Indexed keywords

EID: 0001244469     PISSN: 10485252     EISSN: None     Source Type: Journal    
DOI: 10.1080/10485259608832673     Document Type: Article

References (29)

1. Benghabrit, Y. and Hallin, M. (1992). Optimal rank-based test against first-order superdiagonal bilinear dependence. Journal of Statistical Planning and Inference, 32, 45-61.
2. Box, G. E. P. and Pierce, D. (1970). Distribution of residual autocorrelation in autoregressive integrated moving average time series models. Journal of the American Statistical Association, 65, 1509-1526.
3. Brock, W. A., Dechert, W. D. and Scheinkmann, J. A. (1987). A test for indepedence based on the correlation dimension. Department of Economics, University of Wisconsin.
4. Brock, W. A., Dechert, W. D. Scheinkmann, J. A. and Lebaron, B. (1991). A test of independence based on the correlation dimension. Department of Economics, University of Wisconsin.
5. Chan, N. H. and Tran, L. T. (1992). Nonparametric tests for serial dependence. Journal of Time Series Analysis, 13, 19-28.
6. Chen, R. and Tsay, R. S. (1993). Functional-coefficient autoregressive model. Journal of the American Statistical Association, 88, 298-308.
7. Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of the U. K. inflation. Econometrica, 50, 987-1008.
8. Hall, P. (1984). Central limit theorem for integrated square error of multivariate nonparametric density estimators. Journal of Multivariate Analysis, 14, 1-16.
9. Hallin, M. and Puri, M. L. (1992). Rank tests for time series analysis: A survey. In D. Brillinger et al., Eds: New Directions in Time Series Analysis, Springer: New York, 111-153.
10. Hallin, M. and Puri, M. L. (1994). Aligned rank tests for linear models with autocorrelated error terms. Journal of Multivariate Analysis, 50, 175-238.
11. Härdle, V. and Mammen, E. (1993). Comparing nonparametric versus parametric regression fits. Annals of Statistics, 21, 1926-1948.
12. Hinich, M. (1982). Testing for Gaussianity and linearity of a stationary time series. Journal of Time Series Analysis, 3, 169-176.
13. Hjellvik, V. and Tjøstheim, D. (1995). Nonparametric tests of linearity for time series. Biometrika 82, 351-368.
14. Ljung, G. M. and Box, G. E. P. (1978). On a measure of lack of fit in time series models. Biometrika, 65, 297-303.
15. Luukkonen, R., Saikkonen, P. and Teräsvirta, T. (1988). Testing of linearity in univariate time series. Scandinavian Journal of Statistics, 15, 161-175.
16. Masry, E. and Tjøstheim, D. (1995). Nonparametric estimation and identification of nonlinear ARCH time series. Strong convergence and asymptotic normality. Econometric Theory, 11, 258-289.
17. Mizrach, B. (1991). A simple nonparametric test of independence of order (p). Department of Finance. The Wharton School, Philadelphia.
18. Pinkse, C. A. P. (1993). A general characteristic function based measure applied to serial independence testing. Preprint, London School of Economics.
19. Robinson, P. (1983). Non-parametric estimation for time series models. Journal of Time Series Analysis, 4 185-208.
20. Robinson, P. (1991). Consistent nonparametric entropy-based testing. Review of Economic Studies, 58, 437-453.
21. Silverman, B. W. (1986). Density Estimation for Statistics and Data Analysis. Chapman and Hall: London.
22. Skaug, H. J. and Tjøstheim, D. (1993a). Nonparametric tests of serial independence. In Developments in Time Series Analysis. The Priestley Birthday Volume, T. Subba Rao Ed. Chapman and Hall: London.
23. Skaug, H. J. and Tjøstheim, D. (1993b). A nonparametric test of serial independence based on the empirical distribution function. Biometrika, 80, 591-602.
24. Skaug, H. J. and Tjøstheim, D. (1995). Measures of distance between densities with application to testing for serial independence. Preprint, Department of Mathematics, University of Bergen, to appear in volume in honour of Ted Hannan.
25. Subba Rao, T. and Gabr, M. M. (1980). A test of linearity of stationary time series. Journal of Time Series Analysis, 3, 169-176.
26. Sugihara, G. and May, R. M. (1990). Nonlinear forecasting as a way of distinguishing chaos from measurement error in time series. Nature, 344, 734-741.
27. Teräsvirta, T. Tjøstheim, D. and Granger C. W. J. (1994). Aspects of modeling nonlinear time series. In Handbook of Econometrics, R. F. Engle and D. McFadden Eds., Elsevier: Amsterdam.
28. Tjøstheim, D. and Auestad, B. (1994a). Nonparametric identification of nonlinear time series: Projection. Journal of the American Statistical Association, 89, 1398-1409.
29. Tjøstheim, D. and Auestad, B. (1994b). Nonparametric identification of nonlinear time series: Selecting significant lags. Journal of the American Statistical Association, 89, 1410-1419.