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Fast and compact smoothing on large multidimensional grids

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  • Eilers, Paul H.C.
  • Currie, Iain D.
  • Durban, Maria

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  • Eilers, Paul H.C. & Currie, Iain D. & Durban, Maria, 2006. "Fast and compact smoothing on large multidimensional grids," Computational Statistics & Data Analysis, Elsevier, vol. 50(1), pages 61-76, January.
    • Handle: RePEc:eee:csdana:v:50:y:2006:i:1:p:61-76
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    References listed on IDEAS

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    1. Ruppert,David & Wand,M. P. & Carroll,R. J., 2003. "Semiparametric Regression," Cambridge Books, Cambridge University Press, number 9780521780506.
    2. Arũnas P. Verbyla & Brian R. Cullis & Michael G. Kenward & Sue J. Welham, 1999. "The Analysis of Designed Experiments and Longitudinal Data by Using Smoothing Splines," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 48(3), pages 269-311.
    3. Ruppert,David & Wand,M. P. & Carroll,R. J., 2003. "Semiparametric Regression," Cambridge Books, Cambridge University Press, number 9780521785167.
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    Cited by:

    1. Aguilera Morillo, María del Carmen & Durbán, María & Aguilera, Ana M., 2015. "Penalized functional spatial regression," DES - Working Papers. Statistics and Econometrics. WS 21206, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Aris Perperoglou, 2011. "Fitting survival data with penalized Poisson regression," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(4), pages 451-462, November.
    3. Martin Siebenborn & Julian Wagner, 2021. "A multigrid preconditioner for tensor product spline smoothing," Computational Statistics, Springer, vol. 36(4), pages 2379-2411, December.
    4. Ugarte, M.D. & Goicoa, T. & Militino, A.F. & Durbán, M., 2009. "Spline smoothing in small area trend estimation and forecasting," Computational Statistics & Data Analysis, Elsevier, vol. 53(10), pages 3616-3629, August.
    5. Heim, S. & Fahrmeir, L. & Eilers, P.H.C. & Marx, B.D., 2007. "3D space-varying coefficient models with application to diffusion tensor imaging," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6212-6228, August.
    6. Lee, Dae-Jin & Durbán, María, 2009. "Smooth-CAR mixed models for spatial count data," Computational Statistics & Data Analysis, Elsevier, vol. 53(8), pages 2968-2979, June.
    7. Tomas, Julien & Planchet, Frédéric, 2013. "Multidimensional smoothing by adaptive local kernel-weighted log-likelihood: Application to long-term care insurance," Insurance: Mathematics and Economics, Elsevier, vol. 52(3), pages 573-589.
    8. Y. Andriyana & I. Gijbels & A. Verhasselt, 2018. "Quantile regression in varying-coefficient models: non-crossing quantile curves and heteroscedasticity," Statistical Papers, Springer, vol. 59(4), pages 1589-1621, December.
    9. David O'Donnell & Alastair Rushworth & Adrian W. Bowman & E. Marian Scott & Mark Hallard, 2014. "Flexible regression models over river networks," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 63(1), pages 47-63, January.
    10. Román Mínguez & Roberto Basile & María Durbán, 2020. "An alternative semiparametric model for spatial panel data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 29(4), pages 669-708, December.
    11. Rodríguez-Álvarez, María Xosé & Lee, Dae-Jin & Kneib, Thomas & Durbán, María & Eilers, Paul, 2013. "Fast algorithm for smoothing parameter selection in multidimensional generalized P-splines," DES - Working Papers. Statistics and Econometrics. WS ws133026, Universidad Carlos III de Madrid. Departamento de Estadística.
    12. Mariola Sánchez-González & María Durbán & Dae-Jin Lee & Isabel Cañellas & Hortensia Sixto, 2017. "Smooth additive mixed models for predicting aboveground biomass," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 22(1), pages 23-41, March.
    13. Militino, A.F. & Goicoa, T. & Ugarte, M.D., 2012. "Estimating the percentage of food expenditure in small areas using bias-corrected P-spline based estimators," Computational Statistics & Data Analysis, Elsevier, vol. 56(10), pages 2934-2948.
    14. Sabine Schnabel & Paul Eilers, 2013. "Simultaneous estimation of quantile curves using quantile sheets," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(1), pages 77-87, January.
    15. Lee, Dae-Jin & Durbán, María, 2009. "P-spline anova-type interaction models for spatio-temporal smoothing," DES - Working Papers. Statistics and Econometrics. WS ws093312, Universidad Carlos III de Madrid. Departamento de Estadística.
    16. Ayma Anza, Diego Armando & Durbán, María & Lee, Dae-Jin & Van de Kassteele, Jan, 2016. "Modelling latent trends from spatio-temporally grouped data using composite link mixed models," DES - Working Papers. Statistics and Econometrics. WS 23448, Universidad Carlos III de Madrid. Departamento de Estadística.
    17. Francesca Bruno & Fedele Greco & Massimo Ventrucci, 2016. "Non-parametric regression on compositional covariates using Bayesian P-splines," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(1), pages 75-88, March.
    18. Lee, Dae-Jin & Durbán, María & Eilers, Paul, 2013. "Efficient two-dimensional smoothing with P-spline ANOVA mixed models and nested bases," Computational Statistics & Data Analysis, Elsevier, vol. 61(C), pages 22-37.
    19. María Xosé Rodríguez‐Álvarez & María Durbán & Paul H.C. Eilers & Dae‐Jin Lee & Francisco Gonzalez, 2023. "Multidimensional adaptive P‐splines with application to neurons' activity studies," Biometrics, The International Biometric Society, vol. 79(3), pages 1972-1985, September.
    20. Antonio Gasparrini & Fabian Scheipl & Ben Armstrong & Michael G. Kenward, 2017. "A penalized framework for distributed lag non-linear models," Biometrics, The International Biometric Society, vol. 73(3), pages 938-948, September.
    21. Alastair M. Rushworth & Adrian W. Bowman & Mark J. Brewer & Simon J. Langan, 2013. "Distributed Lag Models for Hydrological Data," Biometrics, The International Biometric Society, vol. 69(2), pages 537-544, June.
    22. Lee, Dae-Jin & Durbán, María, 2008. "Smooth-car mixed models for spatial count data," DES - Working Papers. Statistics and Econometrics. WS ws085820, Universidad Carlos III de Madrid. Departamento de Estadística.
    23. Ayma Anza, Diego Armando & Durbán, María & Lee, Dae-Jin & Eilers, Paul, 2015. "Penalized composite link mixed models for two-dimensional count data," DES - Working Papers. Statistics and Econometrics. WS ws1509, Universidad Carlos III de Madrid. Departamento de Estadística.
    24. Francesca Bruno & Fedele Greco & Massimo Ventrucci, 2016. "Non-parametric regression on compositional covariates using Bayesian P-splines," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 25(1), pages 75-88, March.
    25. Kehui Chen & Pedro Delicado & Hans-Georg Müller, 2017. "Modelling function-valued stochastic processes, with applications to fertility dynamics," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(1), pages 177-196, January.

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