cobs

R package cobs: Constrained B-Splines (Sparse Matrix Based). Qualitatively Constrained (Regression) Smoothing Splines via Linear Programming and Sparse Matrices.

Keywords for this software

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References in zbMATH (referenced in 10 articles )

Showing results 1 to 10 of 10.
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  1. Muggeo, Vito M. R.; Torretta, Federico; Eilers, Paul H. C.; Sciandra, Mariangela; Attanasio, Massimo: Multiple smoothing parameters selection in additive regression quantiles (2021)
  2. Rodrigues, T.; Dortet-Bernadet, J.-L.; Fan, Y.: Simultaneous Fitting of Bayesian penalised quantile splines (2019)
  3. Stasinopoulos, Mikis D.; Rigby, Robert A.; De Bastiani, Fernanda: GAMLSS: a distributional regression approach (2018)
  4. Mhalla, Linda; Chavez-Demoulin, Valérie; Naveau, Philippe: Non-linear models for extremal dependence (2017)
  5. Azadbakhsh, Mahdis; Jankowski, Hanna; Gao, Xin: Computing confidence intervals for log-concave densities (2014)
  6. Xiyue Liao; Mary Meyer: coneproj: An R Package for the Primal or Dual Cone Projections with Routines for Constrained Regression (2014) not zbMATH
  7. Rigby, Ra; Stasinopoulos, Dm; Voudouris, V.: Discussion: a comparison of GAMLSS with quantile regression (2013)
  8. Schnabel, Sabine K.; Eilers, Paul H. C.: Simultaneous estimation of quantile curves using quantile sheets (2013)
  9. Hyndman, Rob J.; Shang, Han Lin: Forecasting functional time series (2009)
  10. Ng, Pin; Maechler, Martin: A fast and efficient implementation of qualitatively constrained quantile smoothing splines (2007)