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The Analysis of Designed Experiments and Longitudinal Data by Using Smoothing Splines

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  1. Murphy, Sean R. & Boschma, Suzanne P. & Harden, Steven, 2022. "A lucerne-digit grass pasture offers herbage production and rainwater productivity equal to a digit grass pasture fertilized with applied nitrogen," Agricultural Water Management, Elsevier, vol. 259(C).
  2. 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.
  3. Dale Zimmerman & Vicente Núñez-Antón & Timothy Gregoire & Oliver Schabenberger & Jeffrey Hart & Michael Kenward & Geert Molenberghs & Geert Verbeke & Mohsen Pourahmadi & Philippe Vieu & Dela Zimmerman, 2001. "Parametric modelling of growth curve data: An overview," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 10(1), pages 1-73, June.
  4. Jan Serroyen & Geert Molenberghs & Marc Aerts & Ellen Vloeberghs & Peter Paul De Deyn & Geert Verbeke, 2010. "Flexible estimation of serial correlation in nonlinear mixed models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(5), pages 833-846.
  5. Øystein Sørensen & Anders M. Fjell & Kristine B. Walhovd, 2023. "Longitudinal Modeling of Age-Dependent Latent Traits with Generalized Additive Latent and Mixed Models," Psychometrika, Springer;The Psychometric Society, vol. 88(2), pages 456-486, June.
  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. Ruixue Du & Hiroshi Yamada, 2020. "Principle of Duality in Cubic Smoothing Spline," Mathematics, MDPI, vol. 8(10), pages 1-19, October.
  8. 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.
  9. Xiaojun Mao & Somak Dutta & Raymond K. W. Wong & Dan Nettleton, 2020. "Adjusting for Spatial Effects in Genomic Prediction," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 25(4), pages 699-718, December.
  10. Camarda, Carlo Giovanni & Durbán, María, 2008. "Goodness of fit in models for mortality data," DES - Working Papers. Statistics and Econometrics. WS ws083909, Universidad Carlos III de Madrid. Departamento de Estadística.
  11. Welham, S.J. & Thompson, R., 2009. "A note on bimodality in the log-likelihood function for penalized spline mixed models," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 920-931, February.
  12. Schnabel, Sabine K. & Eilers, Paul H.C., 2009. "Optimal expectile smoothing," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4168-4177, October.
  13. 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.
  14. Arūnas P. Verbyla & Joanne Faveri & John D. Wilkie & Tom Lewis, 2018. "Tensor Cubic Smoothing Splines in Designed Experiments Requiring Residual Modelling," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 23(4), pages 478-508, December.
  15. Woojoo Lee & Hans‐Peter Piepho & Youngjo Lee, 2021. "Resolving the ambiguity of random‐effects models with singular precision matrix," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 75(4), pages 482-499, November.
  16. Yao, Fang, 2007. "Asymptotic distributions of nonparametric regression estimators for longitudinal or functional data," Journal of Multivariate Analysis, Elsevier, vol. 98(1), pages 40-56, January.
  17. Derick R. Peterson & Hongwei Zhao & Sara Eapen, 2003. "Using Local Correlation in Kernel-Based Smoothers for Dependent Data," Biometrics, The International Biometric Society, vol. 59(4), pages 984-991, December.
  18. Kuparinen, Anna & Björklund, Mats, 2011. "Theory put into practice: An R implementation of the infinite-dimensional model," Ecological Modelling, Elsevier, vol. 222(12), pages 2027-2030.
  19. Nicholas Longford, 2014. "On the inefficiency of the restricted maximum likelihood," Economics Working Papers 1415, Department of Economics and Business, Universitat Pompeu Fabra.
  20. Faustin Habyarimana & Shaun Ramroop, 2015. "Determinants of Poverty of Households: Semi parametric Analysis of Demographic and Health Survey Data from Rwanda," Journal of Economics and Behavioral Studies, AMH International, vol. 7(3), pages 47-55.
  21. Lihui Zhao & Tom Chen & Vladimir Novitsky & Rui Wang, 2021. "Joint penalized spline modeling of multivariate longitudinal data, with application to HIV‐1 RNA load levels and CD4 cell counts," Biometrics, The International Biometric Society, vol. 77(3), pages 1061-1074, September.
  22. Maria Durbán & Iain D. Currie, 2003. "A note on P-spline additive models with correlated errors," Computational Statistics, Springer, vol. 18(2), pages 251-262, July.
  23. Beran, Jan & Liu, Haiyan, 2016. "Estimation of eigenvalues, eigenvectors and scores in FDA models with dependent errors," Journal of Multivariate Analysis, Elsevier, vol. 147(C), pages 218-233.
  24. M. P. Wand, 2003. "Smoothing and mixed models," Computational Statistics, Springer, vol. 18(2), pages 223-249, July.
  25. Davies, Lloyd & Quinn, Helen & Della Bosca, Tony & Alford, Andrew & Griffith, Garry, 2009. "The Economic Effects of Alternate Growth Path and Breed Type Combinations to Meet Beef Market Specifications across Southern Australia," Research Reports 280782, New South Wales Department of Primary Industries Research Economists.
  26. Laurini, Fabrizio & Pauli, Francesco, 2009. "Smoothing sample extremes: The mixed model approach," Computational Statistics & Data Analysis, Elsevier, vol. 53(11), pages 3842-3854, September.
  27. Gilmour, Arthur & Cullis, Brian & Welham, Sue & Gogel, Beverley & Thompson, Robin, 2004. "An efficient computing strategy for prediction in mixed linear models," Computational Statistics & Data Analysis, Elsevier, vol. 44(4), pages 571-586, January.
  28. Philipp F. M. Baumann & Enzo Rossi & Alexander Volkmann, 2020. "What Drives Inflation and How: Evidence from Additive Mixed Models Selected by cAIC," Papers 2006.06274, arXiv.org, revised Aug 2022.
  29. Leontine Alkema & Jin Rou New & Jon Pedersen & Danzhen You & all members of the UN Inter-agency Group for Child Mortality Estimation and its Technical Advisory Group, 2014. "Child Mortality Estimation 2013: An Overview of Updates in Estimation Methods by the United Nations Inter-Agency Group for Child Mortality Estimation," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-13, July.
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