Rejoinder: Regularized regression for categorical data

Bondell HD Reich BJ (2009) Simultaneous factor selection and collapsing levels in ANOVA. Biometrics , 65, 169–77.

Breiman L (2001) Random forests. Machine Learning , 45, 5–32.

Chiquet J Grandvalet Y Charbonnier C (2013) Sparsity with sign-coherent groups of variables via the cooperative-lasso. The Annals of Applied Statistics , 6, 795–830.

Dezeure R Bühlmann P Meier L Meinshausen N (2015) High-dimensional inference: Confidence intervals, p-values and R-software hdi. Statistical Science , 30, 533–58.

Flynn CJ Hurvich CM Simonoff JS (2014) On the sensitivity of the lasso to the number of predictor variables. arXiv preprint arXiv: 1403.4544.

Gertheiss J (2014) Anova for factors with ordered levels. Journal of Agricultural, Biological, and Environmental Statistics , 19, 258–77.

Gertheiss J Hogger S Oberhauser C Tutz G (2011) Selection of ordinally scaled independent variables with applications to international classification of functioning core sets. Journal of the Royal Statistical Society, Series C (Applied Statistics) , 60, 377–96.

Gertheiss J Oehrlein F (2011) Testing relevance and linearity of ordinal predictors. Electronic Journal of Statistics , 5, 1935–59.

Gertheiss J Stelz V Tutz G (2013) Regularization and model selection with categorical covariates. In Lausen B, Van den Poel D and Ultsch A eds., Algorithms from and for Nature and Life , pages 215–222. Berlin/Heidelberg: Springer.

Gertheiss J Tutz G (2009) Penalized regression with ordinal predictors. International Statistical Review , 77, 345–65.

Gertheiss J Tutz G (2010) Sparse modeling of categorial explanatory variables. Annals of Applied Statistics , 4, 2150–80.

Gertheiss J Tutz G (2012) Regularization and model selection with categorial effect modifiers. Statistica Sinica , 22, 957–82.

Hastie T Tibshirani R (1993) Varying-coefficient models. Journal of the Royal Statistical Society, Series B , 55, 757–96.

Hoefling H (2010) A path algorithm for the fused lasso signal approximator. Journal of Computational and Graphical Statistics , 19, 984–1006.

Leitenstorfer F Tutz G (2007) Generalized monotonic regression based on B-splines with an application to air pollution data. Biostatistics , 8, 654–73.

Liaw A Wiener M (2002) Classification and regression by randomforest. R News , 2, 18–22.

Lin D Pramana S Verbeke T Shkedy Z (2014) IsoGene: Order-Restricted Inference for Microarray Experiments. R package version 1.0-23.

Lin D Shkedy Z Yekutieli D Burzykowski T Göhlmann HW Bondt AD Perera T Geerts T Bijnens L (2007) Testing for trends in dose-response microarray experiments: A comparison of several testing procedures, multiplicity and resampling-based inference. Statistical Applications in Genetics and Molecular Biology , 6, article 26.

Meier L Meinshausen N Dezeure R (2014) hdi: High-Dimensional Inference. R package version 0.1–2.

Post J Bondell H (2013) Factor selection and structural identification in the interaction ANOVA model. Biometrics , 69, 70–9.

Pötscher BM Schneider U (2009) On the distribution of the adaptive lasso estimator. Journal of Statistical Planning and Inference , 139, 2775–90.

Pramana S Lin D Haldermans P Shkedy Z Verbeke T De Bondt A Talloen W Göhlmann H Bijnens L (2010) IsoGene: An R package for analyzing dose-response studies in microarray experiments. R Journal , 2/1, 5–12.

Sweeney E Crainiceanu C Gertheiss J (2016) Testing differentially expressed genes in dose-response studies and with ordinal phenotypes. Statistical Applications in Genetics and Molecular Biology , in press.

Tutz G (2012) Regression for Categorical Data . Cambridge: Cambridge University Press.

Tutz G Leitenstorfer F (2007) Generalized smooth monotonic regression in additive modeling. Journal of Computational and Graphical Statistics , 16, 165–88.

Walter SD Feinstein AR Wells CK (1987) Coding ordinal independent variables in multiple regression analysis. American Journal of Epidemiology , 125, 319–23.em