The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
To cite package 'FDboost' itself use the manual (Brockhaus and Ruegamer 2018) and the tutorial (Brockhaus et al. 2017a); to cite functional linear array models use Brockhaus et al. (2015); to cite models with historical effects use Brockhaus et al. (2017b); to cite models with factor-specific historical effects use Ruegamer (2018).
Brockhaus S, Ruegamer D (2018). FDboost: Boosting Functional Regression Models.
Brockhaus S, Scheipl F, Hothorn T, Greven S (2015). “The Functional Linear Array Model.” Statistical Modelling, 15(3), 279–300.
Brockhaus S, Melcher M, Leisch F, Greven S (2017). “Boosting flexible functional regression models with a high number of functional historical effects.” Statistics and Computing, 27(4), 913–926.
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. 1609.06070.
To cite FDboost in publications use:
Brockhaus S, RĂ¼gamer D, Greven S (2020). “Boosting Functional Regression Models with FDboost.” Journal of Statistical Software, 94(10), 1–50. doi:10.18637/jss.v094.i10.
Corresponding BibTeX entries:
@Manual{, title = {FDboost: Boosting Functional Regression Models}, author = {Sarah Brockhaus and David Ruegamer}, year = {2018}, }
@Article{, title = {The Functional Linear Array Model}, author = {Sarah Brockhaus and Fabian Scheipl and Torsten Hothorn and Sonja Greven}, journal = {Statistical Modelling}, year = {2015}, volume = {15}, number = {3}, pages = {279--300}, }
@Article{, author = {Sarah Brockhaus and Michael Melcher and Friedrich Leisch and Sonja Greven}, title = {Boosting flexible functional regression models with a high number of functional historical effects}, journal = {Statistics and Computing}, year = {2017}, volume = {27}, number = {4}, pages = {913--926}, }
@Article{, author = {David Ruegamer and Sarah Brockhaus and Kornelia Gentsch and Klaus Scherer and Sonja Greven}, title = {Boosting factor-specific functional historical models for the detection of synchronization in bioelectrical signals}, journal = {Journal of the Royal Statistical Society: Series C (Applied Statistics)}, eprint = {1609.06070}, year = {2018}, volume = {67}, pages = {621--642}, }
@Article{, title = {Boosting Functional Regression Models with {FDboost}}, author = {Sarah Brockhaus and David R\"ugamer and Sonja Greven}, journal = {Journal of Statistical Software}, year = {2020}, volume = {94}, number = {10}, pages = {1--50}, doi = {10.18637/jss.v094.i10}, }
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.