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Articles

Bootstrap procedures for variance breaks test in time series with a changing trend

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Pages 4609-4627 | Received 29 Mar 2017, Accepted 04 Sep 2017, Published online: 08 Nov 2017

References

  • Bai, J. 1994. Least squares estimation of a shift in linear processes. Journal of Time Series Analysis 15:453–72.
  • Bai, J. 1994. Least squares estimation of a shift in linear processes. Journal of Time Series Analysis 15:453–72.
  • Bai, J. 1997. Estimation of a change point in multiple regression models. Review of Economic and Statistics 79:551–63.
  • Bai, J. 2010. Common breaks in means and variances for panel data. Journal of Econometrics 157:78–92.
  • Berkes, I., E. Gombay, and L. Horvá th. 2009. Testing for changes in the covariance structure of linear processes. Journal of Statistical Planning and Inference 139:2044–63.
  • Billingsley, P. 1968. Convergence of probability measures. New York: John Wiley & Sons.
  • Brockwell, P. J., and R. A. Davis. 1990. Time series: Theory and methods. 2nd ed. New York: Springer-Verlag.
  • Brodsky, B. E., and B. S. Darkhovsky. 1993. Nonparametric method in change point problems. Netherlands: Kluwer Academic Publishers.
  • Brown, R. L., J. Durbin, and J. M. Evans. 1975. Techniques for testing the constancy of regression relationship over time. Journal of the Royal Statistical Society: Series B 37:149–63.
  • Cavaliere, G., and A. M. R. Taylor. 2009. Bootstrap M unit root tests. Econometric Reviews 28:393–421.
  • Csörgő, M., and L. Horváh. 1997. Limit theorem in change-point analysis. Chichester: Wiley.
  • Davidson, J. E. H. 1995. Stochastic limit theory. 2nd ed. UK: Oxford University.
  • Davis, R. A., C. M. T. Lee, and G. A. Rodriguez-Yam. 2006. Stuctural break estimation for nonstationary time series models. Journal of the American Statistical Association 101:223–39.
  • Demetrescu, M., and D. Wied. Residual-based inference on moment hypotheses, with an application to testing for constant correlation, Miemo.
  • Dette, H., W. Wu, and Z. Zhou. Change point analysis of second order characteristics in non-stationary time series, Miemo.
  • Gombay, E., L. Horváth, and M. Hus̆ková. 1996. Estimators and tests for changes in the variance. Statistics and Decisions 14:145–59.
  • Gombay, E., and D. Serban. 2009. Monitoring parameter change in ar(p) time series models. Journal of Multivariate Analysis 4:715–25.
  • Hackl, P., and A. H. Westlund. 1991. Economic structural changes: Analysis and forecasting. Berlin: Springer-Verlag.
  • Horváth, L., P. Kokoszka, and A. Zhang. 2006. Monitoring constancy of variance in conditionally heteroskedastic time series. Econometric Theory 22:373–402.
  • Horváth, L., and J. Steinebach. 2000. Testing for changes in the mean or variance of a stochastic process under weak invariance. Journal of Statistical Planning and Inference 91:365–76.
  • Hsu, D. A., R. B. Miler, and D. W. Wichern. 1974. On the stable paretian behavior of stock-market prices. Journal of the American Statistical Association 69:108–13.
  • Inclán, C., and G. C. Tiao. 1994. Use of cumulative sums of squares for retrospective detection of change of variance. Journal of the American Statistical Association 89:913–23.
  • Kim, S., S. Cho, and S. Lee. 2000. On the cusum test for parameter changes in GARCH(1,1) models. Communication in Statistics - Theory and Methods 29:445–62.
  • Kokoszka, P. S., Parfionovas, A. 2004. Bootstrap unit root tests for heavy tailed time series. Handbook of Computational and Numerical Methods in Finance, Rachev, S. T. (eds). Berlin Heidelberg: Springer Verlag 175–97.
  • Lee, S., O. Na, and S. Na. 2003. On the Cusum squares test for variance change in nonstationary and nonparameteric time series models. Annals of the Institute of Statistical Mathematics 55:467–85.
  • Lee, S., and S. Park. 2001. The cusum of squares test for scale changes in infinite order moving average processes. Scandinavian Journal of Statistics 28:625–42.
  • McMurry, T. L., and D. N. Politis. 2010. Banded and tapered estimates for autocovariance matrices and the linear bootstrap. Journal of Time Series Analysis 31:471–82.
  • Ng, S., and P. Perron. 2001. Lag length selection and the construction of unit root tests with good size and power. Econometrica 69:1519–54.
  • Palm, F. Z., S. Smeekes, and J. P. Urbain. 2008. Bootstrap unit-root tests: comparison and extensions. Journal of Time Series Analysis 29:1519–54.
  • Paparoditis, E., and D. N. Politis. 2003. Residual-based block bootstrap for unit root testing. Econometrica 71:813–55.
  • Park, S., S. Lee, and J. Jeon. 2000. The cusum of squares test for variance changes in infinite order autoregressive models. Journal of Korean Statistical Sociation 29:625–44.
  • Parker, C., E. Paparoditis, and D. N. Politis. 2006. Unit root testing via the stationary bootstrap. Journal of Econometrics 133:601–38.
  • Perron, P. 2006. Dealing with structural breaks. In Palgrave Handbook of Econometrics, vol. 1, ed. by Patterson, K. and Mills, T. C. London: Palgrave Macmillan, 278–352.
  • Perron, P., and X. K. Zhu. 2005. Structural breaks with deterministic and stochastic trends. Journal of Econometrics 129:65–119.
  • Phillips, P. C. B., and V. Solo. 1992. Asymptotic for linear processes. Oxford Bulletin of Economics and Statistics 20:971–1001.
  • Picard, D. 1985. Testing and estimating change-points in time series. Advances in Applied Probability 17:841–67.
  • Psaradskis, Z. 2001. Bootstrap tests for an autoregressive unit root in the presence of weakly dependent errors. Journal of Time Series Analysis 22:577–94.
  • Resnick, S. I. 1986. Point processes, regular variation and weak convergences. Advanced of Applied Probability 18:66–138.
  • Swensen, A. R. 2003. Bootstrapping unit root tests for integrated processes. Journal of Time Series Analysis 24:99–126.
  • Wang, L., and J. Wang. 2006. Change of variance problem for linear process with long memory. Statistical Paper 47:279–98.
  • Zhao, W. Z., Z. M. Xia, and Z. Tian. 2010. Ratio test for variance change point in linear process with long memory. Statistical Paper 51:397–407.

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