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An introduction to function-on-scalar regression

Bauer, Alexander, Fabian Scheipl, Helmut Küchenhoff, and Alice-Agnes Gabriel (2018), An introduction to function-on-scalar regression, Statistical Modelling Journal, 18(3-4), 346–364, doi:10.1177/1471082X17748034.

Function-on-scalar regression models feature a function over some do- main as the response while the regressors are scalars. Collections of time series as well as 2D or 3D images can be considered a functional response. We give a hands-on introduction into a flexible semiparametric approach for function-on-scalar regression, using spatially referenced time series of ground velocity measurements from large-scale simulated earthquake data as a running example. We discuss important practical con- siderations and challenges in the modelling process and outline best practices. The outline of our approach is complemented by comprehensive R code, freely available in the online appendix. This text is aimed at analysts with a basic understanding of generalized regression and spline-based estimation.
Further information
  author = {Alexander Bauer and Fabian Scheipl and Helmut K{\"u}chenhoff and Alice-Agnes Gabriel},
  journal = {Statistical Modelling Journal},
  number = {3-4},
  pages = {346{--}364},
  title = {{An introduction to function-on-scalar regression}},
  volume = {18},
  year = {2018},
  url = {http://journals.sagepub.com/doi/abs/10.1177/1471082X17748034},
  doi = {10.1177/1471082X17748034},
%0 Journal Article
%A Bauer, Alexander
%A Scheipl, Fabian
%A Küchenhoff, Helmut
%A Gabriel, Alice-Agnes
%D 2018
%N 3-4
%V 18
%J Statistical Modelling Journal
%P 346–364
%T An introduction to function-on-scalar regression
%U http://journals.sagepub.com/doi/abs/10.1177/1471082X17748034
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Printed 26. Sep 2020 17:27