References
- Antoniadis, A., G. Gregoire, and I. W. McKeague. 1994. Wavelet methods for curve estimation. Journal of the American Statistical Association 428:1340–53.
- Buonaccorsi, J. P. 2010. Measurement error: Models, methods and applications. New York: Chapman and Hall.
- Cai, Z. 2007. Trending time-varying coefficient time series models with serially correlated errors. Journal of Econometrics 136:163–88.
- Carroll, R. J., D. Ruppert, L. A. Stefanski, and C. Crainiceanu. 2006. Measurement error in nonlinear models: A modern perspective. 2nd ed. New York: Chapman and Hall.
- Chang, Y., and E. Martinez-Chombo. 2003. Electricity demand analysis using cointegration and error-correction models with time varying parameters: The Mexican case. Working paper, Department of Economics, Rice University.
- Fan, G. L., H. Y. Liang, and J. F. Wang. 2013. Statistical inference for partially time-varying coefficient errors-in-variables models. Journal of Statistical Planning and Inference 143:505–19.
- Fan, J., and Q. Yao. 2003. Nonlinear time series: Nonparametric and parametric methods. New York: Springer.
- Fuller, W. A. 1987. Measurement error models. New York: Wiley.
- Hall, P., and C. C. Heyde. 1980. Martingale limit theory and its applications. New York: Academic Press.
- Härdle, W., and T. M. Stoker. 1989. Investigating smooth multiple regression by the method of average derivatives. Journal of the American Statistical Association 84:986–95.
- Hoover, D. R., J. A. Rice, C. O. Wu, and L. P. Yang. 1998. Nonparametric smoothing estimates of time-varying coefficient models with longitudinal data. Biometrika 85:809–22.
- Li, D., J. Chen, and Z. Lin. 2011. Statistical inference in partially time-varying coefficient models. Journal of Statistical Planning and Inference 141:995–1013.
- Li, L., and T. Greene. 2008. Varying coefficients model with measurement error. Biometrics 64:519–26.
- Liang, H., W. Härdle, and R. J. Carroll. 1999. Estimation in a semiparametric partially linear errors-in-variables model. The Annals of Statistics 27:1519–35.
- Lin, Z. Y., and C. R. Lu. 1996. Limit theory for mixing dependent random variables. Beijing: Science Press and K.A.P.
- Lu, Y., and Z. Li. 2009. Wavelet estimation in varying-coefficient models. Chinese Journal of Applied Probability 25:409–20.
- Phillips, P. C. B. 2001. Trending time series and macroeconomic activity: Some present and future challenges. Journal of Econometrics 100:21–27.
- Robinson, P. M. 1989. Nonparametric estimation of time-varying parameters. In Statistical analysis and forecasting of economic structural change, ed. P. Hackl, 164–253. Berlin: Springer.
- Vidakovic, B. 1999. Statistical modeling by wavelet. New York: John Wiley & Sons Inc.
- Wang, K. 2003. Asset pricing with conditioning information: A new test. The Journal of Finance 58:161–96.
- Wei, C. H. 2011. Estimation in varying-coefficient errors-in-variables models with missing response variables. Communication in Statistics: Simulation and Computation 40:383–93.
- You, J. H., Y. Zhou, and G. M. Chen. 2006. Corrected local polynomial estimation in varying-coefficient models with measurement errors. The Canadian Journal of Statistics 34:391–410.
- Zhou, X., and J. You. 2004. Wavelet estimation in varying-coefficient partially linear regression models. Statistics and Probability Letters 68:91–104.
- Zhou, X. C., and J. G. Lin. 2013a. Asymptotic properties of wavelet estimators in semiparametric regression models under dependent errors. Journal of Multivariate Analysis 122:251–70.
- Zhou, X. C., and J. G. Lin. 2013b. On complete convergence for strong mixing sequences. Stochastics An International Journal of Probability and Stochastic Processes 85:262–71.