References
- Chen, L., Chen, M. and Peng, M. (2009). Conditional variance estimation in heteroscedastic regression models. Journal of Statistical Planning and Inference, 139, 236-245. https://doi.org/10.1016/j.jspi.2008.04.020
- Fan, J. and Gijbels, I. (1996). Local polynomial modelling and its application, Chapman and Hall, London.
- Gasser, T., Sroka, L. and Jennen-Steinmetz, C. (1986). Residual variance and residual pattern in nonlinear regression. Biometrika, 73, 625-634. https://doi.org/10.1093/biomet/73.3.625
- Gregoire, G. and Hamrouni, Z. (2002). Change point estimation by local linear smoothing. Journal of Multivariate Analysis, 83, 56-83. https://doi.org/10.1006/jmva.2001.2038
- Hall, P. and Carroll, R. J. (1989). Variance function estimation in regression: The effect of estimating the mean. Journal of the Royal Statistical Society B, 51, 3-14.
- Hall, P., Kay, J. W. and Titterington, D. M. (1990). Asymptotically optimal difference-based estimation of variance in nonparametric regression. Biometrika, 77, 521-528. https://doi.org/10.1093/biomet/77.3.521
- Huh, J. (2005). Nonparametric detection of a discontinuity point in the variance function with the second moment function. Journal of the Korean Data & Information Science Society, 16, 591-601.
- Huh, J. (2009). Testing a discontinuity point in the log-variance function based on likelihood. Journal of the Korean Data & Information Science Society, 20, 1-9.
- Huh, J. (2010). Detection of a change point based on local-likelihood. Journal of Multivariate Analysis, 101, 1681-1700. https://doi.org/10.1016/j.jmva.2010.02.007
- Huh, J. (2012a). Bandwidth selection for discontinuity point estimation in density. Journal of the Korean Data & Information Science Society, 23, 79-87. https://doi.org/10.7465/jkdi.2012.23.1.079
- Huh, J. (2012b). Bandwidth selections based on cross-validation for estimation of a discontinuity point in density. Journal of the Korean Data & Information Science Society, 23, 765-775. https://doi.org/10.7465/jkdi.2012.23.4.765
-
Huh, J. (2013). Estimation of a change point in the variance function based on the
${\chi}^{2}$ -distribution. Preprint. - Huh, J. and Carriere, K. C. (2002). Estimation of regression functions with a discontinuity in a derivative with local polynomial fits. Statistics and Probability Letters, 56, 329-343. https://doi.org/10.1016/S0167-7152(02)00017-2
- Huh, J. and Park, B. U. (2004). Detection of change point with local polynomial fits for random design case. Australian and New Zealand Journal of Statistics, 46, 425-441. https://doi.org/10.1111/j.1467-842X.2004.00340.x
- Kang, K. H. and Huh, J. (2006). Nonparametric estimation of the variance function with a change point. Journal of the Korean Data & Information Science Society, 35, 1-24.
- Loader, C. R. (1996). Change point estimation using nonparametric regression. Annals of Statistics, 24, 1667-1678. https://doi.org/10.1214/aos/1032298290
- Muller, H G. (1992). Change-points in nonparametric regression analysis. Annals of Statistics, 20, 737-761. https://doi.org/10.1214/aos/1176348654
- Muller, H. G. and Stadtmuller, U. (1987). Estimation of heteroscedasticity in regression analysis. Annals of Statistics, 15, 610-625. https://doi.org/10.1214/aos/1176350364
- Rice, J. (1984). Bandwidth choice for nonparametric regression. Annals of Statistics, 12, 1215-1230. https://doi.org/10.1214/aos/1176346788
- Ruppert, D., Wand, M. P., Holst, U. and Hossjer, O. (1997). Local polynomial variance-function estimation. Technomtrics, 39, 262-273. https://doi.org/10.1080/00401706.1997.10485117
- Yu, K. and Jones, M. C. (2004). Likelihood-based local linear estimation of the conditional variance function. Journal of the American Statistical Association, 99, 139-144. https://doi.org/10.1198/016214504000000133
Cited by
- Nonparametric estimation of the discontinuous variance function using adjusted residuals vol.27, pp.1, 2016, https://doi.org/10.7465/jkdi.2016.27.1.111
- 점프크기추정량에 의한 수정된 로그잔차를 이용한 불연속 로그분산함수의 추정 vol.30, pp.2, 2014, https://doi.org/10.5351/kjas.2017.30.2.259