IDEAS home Printed from https://ideas.repec.org/r/eee/csdana/v51y2007i5p2542-2558.html
   My bibliography  Save this item

Robust specification of the roughness penalty prior distribution in spatially adaptive Bayesian P-splines models

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Patricio Maturana-Russel & Renate Meyer, 2021. "Bayesian spectral density estimation using P-splines with quantile-based knot placement," Computational Statistics, Springer, vol. 36(3), pages 2055-2077, September.
  2. Klein, Nadja & Denuit, Michel & Lang, Stefan & Kneib, Thomas, 2014. "Nonlife ratemaking and risk management with Bayesian generalized additive models for location, scale, and shape," Insurance: Mathematics and Economics, Elsevier, vol. 55(C), pages 225-249.
  3. Jaeger, Jonathan & Lambert, Philippe, 2012. "On the use of adhesion parameters to validate models specified using systems of affine differential equations," LIDAM Discussion Papers ISBA 2012018, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  4. Bremhorst, Vincent & Lambert, Philippe, 2016. "Flexible estimation in cure survival models using Bayesian P-splines," Computational Statistics & Data Analysis, Elsevier, vol. 93(C), pages 270-284.
  5. Nadja Klein & Thomas Kneib & Stefan Lang, 2015. "Bayesian Generalized Additive Models for Location, Scale, and Shape for Zero-Inflated and Overdispersed Count Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 405-419, March.
  6. Klein, Nadja & Denuit, Michel & Lang, Stefan & Kneib, Thomas, 2013. "Nonlife Ratemaking and Risk Management with Bayesian Additive Models for Location, Scale and Shape," LIDAM Discussion Papers ISBA 2013045, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  7. Lambert, Philippe, 2007. "Archimedean copula estimation using Bayesian splines smoothing techniques," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6307-6320, August.
  8. Jaeger, Jonathan & Lambert, Philippe, 2012. "Bayesian penalized smoothing approaches in models specified using affine differential equations with unknown error distributions," LIDAM Discussion Papers ISBA 2012017, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  9. Jing Huang & Ying Yuan & David Wetter, 2019. "Latent Class Dynamic Mediation Model with Application to Smoking Cessation Data," Psychometrika, Springer;The Psychometric Society, vol. 84(1), pages 1-18, March.
  10. Stefan Lang & Nikolaus Umlauf & Peter Wechselberger & Kenneth Harttgen & Thomas Kneib, 2012. "Multilevel structured additive regression," Working Papers 2012-07, Faculty of Economics and Statistics, Universität Innsbruck.
  11. Felix Heinzl & Ludwig Fahrmeir & Thomas Kneib, 2012. "Additive mixed models with Dirichlet process mixture and P-spline priors," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(1), pages 47-68, January.
  12. Nadja Klein & Michel Denuit & Stefan Lang & Thomas Kneib, 2013. "Nonlife Ratemaking and Risk Management with Bayesian Additive Models for Location, Scale and Shape," Working Papers 2013-24, Faculty of Economics and Statistics, Universität Innsbruck.
  13. Belitz, Christiane & Lang, Stefan, 2008. "Simultaneous selection of variables and smoothing parameters in structured additive regression models," Computational Statistics & Data Analysis, Elsevier, vol. 53(1), pages 61-81, September.
  14. Gressani, Oswaldo & Lambert, Philippe, 2021. "Laplace approximations for fast Bayesian inference in generalized additive models based on P-splines," Computational Statistics & Data Analysis, Elsevier, vol. 154(C).
  15. Lambert, Philippe & Kreyenfeld, Michaela, 2023. "Exogenous time-varying covariates in double additive cure survival model with application to fertility," LIDAM Discussion Papers ISBA 2023006, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  16. Yang, Lianqiang & Hong, Yongmiao, 2017. "Adaptive penalized splines for data smoothing," Computational Statistics & Data Analysis, Elsevier, vol. 108(C), pages 70-83.
  17. Gressani, Oswaldo & Lambert, Philippe, 2016. "Fast Bayesian inference in semi-parametric P-spline cure survival models using Laplace approximations," LIDAM Discussion Papers ISBA 2016041, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  18. Bremhorst, Vincent & Kreyenfeld, Michaela & Lambert, Philippe, 2017. "Nonparametric double additive cure survival models: an application to the estimation of the nonlinear effect of age at first parenthood on fertility progression," LIDAM Discussion Papers ISBA 2017004, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  19. Lambert, Philippe & Eilers, Paul H.C., 2009. "Bayesian density estimation from grouped continuous data," Computational Statistics & Data Analysis, Elsevier, vol. 53(4), pages 1388-1399, February.
  20. Lambert, Philippe & Gressani, Oswaldo, 2022. "Penalty parameter selection and asymmetry corrections to Laplace approximations in Bayesian P-splines models," LIDAM Discussion Papers ISBA 2022030, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  21. Staudenmayer, John & Ruppert, David & Buonaccorsi, John P., 2008. "Density Estimation in the Presence of Heteroscedastic Measurement Error," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 726-736, June.
  22. Strasak, Alexander M. & Umlauf, Nikolaus & Pfeiffer, Ruth M. & Lang, Stefan, 2011. "Comparing penalized splines and fractional polynomials for flexible modelling of the effects of continuous predictor variables," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1540-1551, April.
  23. Gressani, Oswaldo & Lambert, Philippe, 2018. "Fast Bayesian inference using Laplace approximations in a flexible promotion time cure model based on P-splines," Computational Statistics & Data Analysis, Elsevier, vol. 124(C), pages 151-167.
  24. Bremhorst, Vincent & Lambert, Philippe, 2013. "Flexible estimation in cure survival models using Bayesian P-splines," LIDAM Discussion Papers ISBA 2013039, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  25. Philippe Lambert & Vincent Bremhorst, 2020. "Inclusion of time‐varying covariates in cure survival models with an application in fertility studies," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(1), pages 333-354, January.
  26. Vincent Bremhorst & Michaela Kreyenfeld & Philippe Lambert, 2016. "Fertility progression in Germany: An analysis using flexible nonparametric cure survival models," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 35(18), pages 505-534.
  27. Lambert, Philippe, 2011. "Smooth semiparametric and nonparametric Bayesian estimation of bivariate densities from bivariate histogram data," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 429-445, January.
  28. Eleni†Rosalina Andrinopoulou & Paul H. C. Eilers & Johanna J. M. Takkenberg & Dimitris Rizopoulos, 2018. "Improved dynamic predictions from joint models of longitudinal and survival data with time†varying effects using P†splines," Biometrics, The International Biometric Society, vol. 74(2), pages 685-693, June.
  29. Scheipl, Fabian & Kneib, Thomas, 2009. "Locally adaptive Bayesian P-splines with a Normal-Exponential-Gamma prior," Computational Statistics & Data Analysis, Elsevier, vol. 53(10), pages 3533-3552, August.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.