Included density-on-scalar regression in package description

Author: Eva2703

R/FDboost-package.R

@@ -10,10 +10,12 @@
 #' This package is intended to fit regression models with functional variables. 
 #' It is possible to fit models with functional response and/or functional covariates, 
 #' resulting in scalar-on-function, function-on-scalar and function-on-function regression. 
+#' Furthermore, the package can be used to fit density-on-scalar regression models.
 #' Details on the functional regression models that can be fitted with \pkg{FDboost}
 #' can be found in Brockhaus et al. (2015, 2017, 2018) and Ruegamer et al. (2018).  
 #' A hands-on tutorial for the package can be found 
 #' in Brockhaus, Ruegamer and Greven (2017), see \url{https://arxiv.org/abs/1705.10662}.
+#' For density-on-scalar regression models see Maier et al. (2021).
 #' 
 #' Using component-wise gradient boosting as fitting procedure, \pkg{FDboost} relies on 
 #' the R package \pkg{mboost} (Hothorn et al., 2017). 
@@ -50,6 +52,10 @@
 #' A Hands-on Tutorial Using the R Package mboost. Computational Statistics, 29, 3-35. 
 #' \url{https://cran.r-project.org/package=mboost/vignettes/mboost_tutorial.pdf}
 #' 
+#' Maier, E.-M., Stoecker, A., Fitzenberger, B., Greven, S. (2021):
+#' Additive Density-on-Scalar Regression in Bayes Hilbert Spaces with an Application to Gender Economics.
+#' arXiv preprint arXiv:2110.11771.
+#' 
 #' Ruegamer D., Brockhaus, S., Gentsch K., Scherer, K., Greven, S. (2018). 
 #' Boosting factor-specific functional historical models for the detection of synchronization in bioelectrical signals. 
 #' Journal of the Royal Statistical Society: Series C (Applied Statistics), 67, 621-642.