1 |
Hall, P., Kay, J. W. and Titterinton, D. M. (1990). Asymptotically optimal difference-based estimator of variance in nonparametric regression. Biometrika, 77, 521-528.
DOI
ScienceOn
|
2 |
Carter, C. K. and Eagleson, G. K. (1992). A comparison of variance estimators in nonparametric regression. Journal of the Royal Statistical Society: Series B, 54, 773-780.
|
3 |
Dette, H., Munk, A. and Wagner, T. (1998). Estimating the variance in nonparametric regression-What is a reasonable choice? Journal of the Royal Statistical Society: Series B, 60, 751-764.
DOI
ScienceOn
|
4 |
Rice, J. A. (1984). Bandwidth choice for nonparametric regression. Annals of Statistics, 12, 1215-1220.
DOI
ScienceOn
|
5 |
Tong, T. andWang, Y. (2005). Estimating residual variance in nonparametric regression using least squares. Biometrika, 92, 821-830.
DOI
ScienceOn
|
6 |
Wahba, G. (1990). Spline models for observational data, CBMS-NSF Regional Conference Series in Applied Mathematics, Vol. 59, SIAM, Philadelphia.
|
7 |
Park, C. G. (2008). A note on a Bayesian approach to the choice of wavelet basis functions at each resolution level. Journal of the Korean Data & Information Science Society,19, 1465-1476.
|
8 |
Muller, U., Schick, A. and Wefelmeyer, W. (2003). Estimating the error variance in nonparametric regression by a covariate-matched U-statistic. Statistics, 37, 179-188.
DOI
ScienceOn
|
9 |
Neumann, M. H. (1994). Fully data-driven nonparametric variance estimators. Statistics, 25, 189-212.
DOI
|
10 |
Park, C. G. (2009). An estimator of the mean of the squared functions for a nonparametric regression. Journal of the Korean Data & Information Science Society, 20, 577-585.
|
11 |
Park, C. G., Kim, Y. H. and Yang, W. Y. (2004). Determinacy on a maximum resolution in wavelet series. Journal of the Korean Data & Information Science Society, 15, 467-476.
|
12 |
Gasser, T., Sroka, L. and Jennen-Steinmetz, C. (1986). Residual variance and residual pattern in nonlinear regression. Biometrika, 73, 625-633.
DOI
ScienceOn
|
13 |
Hall, P. and Carroll, R. J. (1989). Variance function estimation in regression: The effect of estimating the mean. Journal of the Royal Statistical Society: Series B, 51, 3-14.
|