Some Guidelines For Using Nonparametric Methods For Modeling Data From Response Surface Designs
暂无分享,去创建一个
[1] G. Vining,et al. Response Surfaces for the Mean and Variance Using a Nonparametric Approach , 1998 .
[2] G. S. Watson,et al. Smooth regression analysis , 1964 .
[3] Derek J. Pike,et al. Empirical Model‐building and Response Surfaces. , 1988 .
[4] George E. P. Box,et al. Empirical Model‐Building and Response Surfaces , 1988 .
[5] B. Yandell. Spline smoothing and nonparametric regression , 1989 .
[6] H. Müller,et al. Estimating regression functions and their derivatives by the kernel method , 1984 .
[7] Jianqing Fan,et al. Local polynomial modelling and its applications , 1994 .
[8] Raymond H. Myers,et al. Response Surface Methodology--Current Status and Future Directions , 1999 .
[9] E. Nadaraya,et al. Some New Estimates for Distribution Functions , 1964 .
[10] M. Wand,et al. Multivariate Locally Weighted Least Squares Regression , 1994 .
[11] Douglas C. Montgomery,et al. A Nonlinear Programming Solution to the Dual Response Problem , 1993 .
[12] R. Eubank. Nonparametric Regression and Spline Smoothing , 1999 .
[13] Theo Gasser,et al. Finite-Sample Variance of Local Polynomials: Analysis and Solutions , 1996 .
[14] Efficient Bandwidth Selection in Non-parametric Regression , 2003 .
[15] Wanzhu Tu,et al. Dual response surface optimization , 1995 .
[16] Jianqing Fan,et al. Data‐Driven Bandwidth Selection in Local Polynomial Fitting: Variable Bandwidth and Spatial Adaptation , 1995 .