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Christian Schellhase

Personal Details

First Name:Christian
Middle Name:
Last Name:Schellhase
Suffix:
RePEc Short-ID:psc656
[This author has chosen not to make the email address public]

Affiliation

Fakultät für Wirtschaftswissenschaften
Universität Bielefeld

Bielefeld, Germany
http://www.wiwi.uni-bielefeld.de/

: 0521/106-3821

Postfach 100131, 33501 Bielefeld
RePEc:edi:fwbiede (more details at EDIRC)

Research output

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Jump to: Articles

Articles

  1. Göran Kauermann & Christian Schellhase & David Ruppert, 2013. "Flexible Copula Density Estimation with Penalized Hierarchical B-splines," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(4), pages 685-705, December.
  2. Christian Schellhase & Göran Kauermann, 2012. "Density estimation and comparison with a penalized mixture approach," Computational Statistics, Springer, vol. 27(4), pages 757-777, December.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Articles

  1. Göran Kauermann & Christian Schellhase & David Ruppert, 2013. "Flexible Copula Density Estimation with Penalized Hierarchical B-splines," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 40(4), pages 685-705, December.

    Cited by:

    1. Luciana Dalla Valle & Maria Elena De Giuli & Claudia Tarantola & Claudio Manelli, 2014. "Default Probability Estimation via Pair Copula Constructions," Papers 1405.1309, arXiv.org, revised Aug 2015.
    2. Nagler, Thomas & Czado, Claudia, 2016. "Evading the curse of dimensionality in nonparametric density estimation with simplified vine copulas," Journal of Multivariate Analysis, Elsevier, vol. 151(C), pages 69-89.
    3. Marra, Giampiero & Radice, Rosalba, 2017. "Bivariate copula additive models for location, scale and shape," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 99-113.
    4. Gery Geenens & Arthur Charpentier & Davy Paindaveine, 2014. "Probit Transformation for Nonparametric Kernel Estimation of the Copula Density," Working Papers ECARES ECARES 2014-23, ULB -- Universite Libre de Bruxelles.
    5. Nadja Klein & Thomas Kneib & Giampiero Marra & Rosalba Radice & Slawa Rokicki & Mark E. McGovern, 2018. "Mixed Binary-Continuous Copula Regression Models with Application to Adverse Birth Outcomes," CHaRMS Working Papers 18-06, Centre for HeAlth Research at the Management School (CHaRMS).
    6. Giampiero Marra & Rosalba Radice & Till Bärnighausen & Simon N. Wood & Mark E. McGovern, 2016. "A Simultaneous Equation Approach to Estimating HIV Prevalence with Non-Ignorable Missing Responses," Economics Working Papers 16-02, Queen's Management School, Queen's University Belfast.
    7. Smith, Michael Stanley & Maneesoonthorn, Worapree, 2018. "Inversion copulas from nonlinear state space models with an application to inflation forecasting," International Journal of Forecasting, Elsevier, vol. 34(3), pages 389-407.

  2. Christian Schellhase & Göran Kauermann, 2012. "Density estimation and comparison with a penalized mixture approach," Computational Statistics, Springer, vol. 27(4), pages 757-777, December.

    Cited by:

    1. Roland Langrock & Thomas Kneib & Alexander Sohn & Stacy L. DeRuiter, 2015. "Nonparametric inference in hidden Markov models using P-splines," Biometrics, The International Biometric Society, vol. 71(2), pages 520-528, June.
    2. Luciana Dalla Valle & Maria Elena De Giuli & Claudia Tarantola & Claudio Manelli, 2014. "Default Probability Estimation via Pair Copula Constructions," Papers 1405.1309, arXiv.org, revised Aug 2015.
    3. Roland Langrock & Timo Adam & Vianey Leos‐Barajas & Sina Mews & David L. Miller & Yannis P. Papastamatiou, 2018. "Spline‐based nonparametric inference in general state‐switching models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 72(3), pages 179-200, August.
    4. Shang, Han Lin, 2013. "Bayesian bandwidth estimation for a nonparametric functional regression model with unknown error density," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 185-198.
    5. Christian Schellhase & Torben Kuhlenkasper, 2017. "Semi-parametric estimation of income mobility with D‑vines using bivariate penalised splines," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 11(2), pages 107-134, October.
    6. Jaspers, Stijn & Aerts, Marc & Verbeke, Geert & Beloeil, Pierre-Alexandre, 2014. "A new semi-parametric mixture model for interval censored data, with applications in the field of antimicrobial resistance," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 30-42.
    7. Roland Langrock & Théo Michelot & Alexander Sohn & Thomas Kneib, 2015. "Semiparametric stochastic volatility modelling using penalized splines," Computational Statistics, Springer, vol. 30(2), pages 517-537, June.

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