Main Article Content
Abstract
Keywords
Article Details
References
- G. Wahba, Spline Models for Observational Data, SIAM, CBMS-NSF Regional Conference Series in Applied Mathematics, Philadelphia, 1990, Vol. 59.
- W. Hardle, Applied Nonparametric Regression, Springer-Verlag, Berlin, 1994.
- K. Doksum, Y.J. Koo, On Spline Estimators and Prediction Intervals in Nonparametric Regression, Computational Statistics and Data Analysis 35 (2000) 67 – 82.
- M. P. Wand, A Comparison of Regression Spline Smoothing Procedures, Departments of Biostatistics, School of Public Health, Harvard, 2005.
- Z. J. Huang, Local Asymptotic for Polynomial Spline Regression, The Annual Statistics 31 (2003) 1600-1635.
- T. J. Hastie, R.J. Tibshirani, Generalized Additive Models, Chapman & Hall, London, 1990.
- R. Eubank, Spline Smoothing and Nonparametric Regression, Marcel Dekker, New York, 1988.
- N. S. Wood, Generalized Additive Models: an Introduction With R, Boca Raton: Chapman & Hall/CRC, 2006.
- J. Wang, L, Yang, Polynomial Spline Confidence Bands for Regression Curves, Statistica Sinica 19 (2009) 325-342.
- P. Craven, G. Wahba, Smoothing Noisy Data with Spline Functions: Estimating the Correct, Degree of Smoothing by the Method of Generalized Cross-Validation, Numer Math University of Wisconsin. 31 (1979) 377-403.
- T. C. M. Lee, Smoothing Parameter Selection for Smoothing Splines: a Simulation Study, Computational Statistic & Data Analysis 42 (2003) 139-148.
- BPS-Statistics. https://www.bps.go.id/linkTableDinamis/view/id/815, accessed on May 19, 2019.
References
G. Wahba, Spline Models for Observational Data, SIAM, CBMS-NSF Regional Conference Series in Applied Mathematics, Philadelphia, 1990, Vol. 59.
W. Hardle, Applied Nonparametric Regression, Springer-Verlag, Berlin, 1994.
K. Doksum, Y.J. Koo, On Spline Estimators and Prediction Intervals in Nonparametric Regression, Computational Statistics and Data Analysis 35 (2000) 67 – 82.
M. P. Wand, A Comparison of Regression Spline Smoothing Procedures, Departments of Biostatistics, School of Public Health, Harvard, 2005.
Z. J. Huang, Local Asymptotic for Polynomial Spline Regression, The Annual Statistics 31 (2003) 1600-1635.
T. J. Hastie, R.J. Tibshirani, Generalized Additive Models, Chapman & Hall, London, 1990.
R. Eubank, Spline Smoothing and Nonparametric Regression, Marcel Dekker, New York, 1988.
N. S. Wood, Generalized Additive Models: an Introduction With R, Boca Raton: Chapman & Hall/CRC, 2006.
J. Wang, L, Yang, Polynomial Spline Confidence Bands for Regression Curves, Statistica Sinica 19 (2009) 325-342.
P. Craven, G. Wahba, Smoothing Noisy Data with Spline Functions: Estimating the Correct, Degree of Smoothing by the Method of Generalized Cross-Validation, Numer Math University of Wisconsin. 31 (1979) 377-403.
T. C. M. Lee, Smoothing Parameter Selection for Smoothing Splines: a Simulation Study, Computational Statistic & Data Analysis 42 (2003) 139-148.
BPS-Statistics. https://www.bps.go.id/linkTableDinamis/view/id/815, accessed on May 19, 2019.