Smoothing Spline Models with Correlated Random Errors
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[1] N. Aronszajn. Theory of Reproducing Kernels. , 1950 .
[2] G. Wahba,et al. Some results on Tchebycheffian spline functions , 1971 .
[3] T. W. Anderson,et al. Statistical analysis of time series , 1972 .
[4] David A. Harville,et al. Extension of the Gauss-Markov Theorem to Include the Estimation of Random Effects , 1976 .
[5] G. Wahba. Bayesian "Confidence Intervals" for the Cross-validated Smoothing Spline , 1983 .
[6] G. Wahba. A Comparison of GCV and GML for Choosing the Smoothing Parameter in the Generalized Spline Smoothing Problem , 1985 .
[7] J. Hart,et al. Kernel Regression Estimation Using Repeated Measurements Data , 1986 .
[8] R. Jennrich,et al. Unbalanced repeated-measures models with structured covariance matrices. , 1986, Biometrics.
[9] Grace Wahba,et al. Testing the (Parametric) Null Model Hypothesis in (Semiparametric) Partial and Generalized Spline Models , 1988 .
[10] B. Yandell. Spline smoothing and nonparametric regression , 1989 .
[11] M. C. Jones,et al. Spline Smoothing and Nonparametric Regression. , 1989 .
[12] M. Hutchinson,et al. ON SPLINE SMOOTHING WITH AUTOCORRELATED ERRORS , 1989 .
[13] J. Raz,et al. Selecting the smoothing parameter for estimation of slowly changing evoked potential signals. , 1989, Biometrics.
[14] Scott L. Zeger,et al. A Frequency Domain Selection Criterion for Regression with Autocorrelated Errors , 1990 .
[15] Naomi Altman,et al. Kernel Smoothing of Data with Correlated Errors , 1990 .
[16] G. Wahba. Spline models for observational data , 1990 .
[17] Grace Wahba,et al. Spline Models for Observational Data , 1990 .
[18] R. Tibshirani,et al. Generalized Additive Models , 1991 .
[19] G. Robinson. That BLUP is a Good Thing: The Estimation of Random Effects , 1991 .
[20] Robert Kohn,et al. The Performance of Cross-Validation and Maximum Likelihood Estimators of Spline Smoothing Parameters , 1991 .
[21] J. Hart. Kernel regression estimation with time series errors , 1991 .
[22] Chong Gu,et al. Cross-Validating Non-Gaussian Data , 1992 .
[23] T. Gasser,et al. Choice of bandwidth for kernel regression when residuals are correlated , 1992 .
[24] R. Kohn,et al. Nonparametric spline regression with autoregressive moving average errors , 1992 .
[25] G. Wahba,et al. Smoothing Spline ANOVA with Component-Wise Bayesian “Confidence Intervals” , 1993 .
[26] Chong Gu,et al. Smoothing spline density estimation: theory , 1993 .
[27] B. Silverman,et al. Nonparametric Regression and Generalized Linear Models: A roughness penalty approach , 1993 .
[28] G. Wahba,et al. Semiparametric Analysis of Variance with Tensor Product Thin Plate Splines , 1993 .
[29] Jeffrey D. Hart,et al. Automated Kernel Smoothing of Dependent Data by Using Time Series Cross‐Validation , 1994 .
[30] B. Silverman,et al. Nonparametric regression and generalized linear models , 1994 .
[31] B. Silverman,et al. Nonparametric Regression and Generalized Linear Models: A roughness penalty approach , 1993 .
[32] Behavior near zero of the distribution of GCV smoothing parameter estimates , 1995 .
[33] G. Wahba,et al. Smoothing spline ANOVA for exponential families, with application to the Wisconsin Epidemiological Study of Diabetic Retinopathy : the 1994 Neyman Memorial Lecture , 1995 .