2018
DOI: 10.1177/1471082x17748034
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An introduction to semiparametric function-on-scalar regression

Abstract: Function-on-scalar regression models feature a function over some domain as the response while the regressors are scalars. Collections of time series as well as 2D or 3D images can be considered as functional responses. We provide a hands-on introduction for 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 considerations and … Show more

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Cited by 17 publications
(11 citation statements)
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References 41 publications
(82 reference statements)
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“…To this end, dynamic rupture simulations can reach high spatial and temporal resolution of increasingly complex geometrical and physical modelling components (e.g. Bauer et al 2017;Wollherr et al 2019). SeisSol is verified with a wide range of community benchmarks, including dipping and branching fault geometries, laboratory derived friction laws, as well as heterogeneous on-fault initial stresses and material properties (de la Puente et al 2009;Pelties et al 2012Pelties et al , 2013Pelties et al , 2014Wollherr et al 2018) in line with the SCEC/USGS Dynamic Rupture Code Verification exercises (Harris et al 2011(Harris et al , 2018.…”
Section: Earthquake-tsunami Coupled Modelingmentioning
confidence: 93%
“…To this end, dynamic rupture simulations can reach high spatial and temporal resolution of increasingly complex geometrical and physical modelling components (e.g. Bauer et al 2017;Wollherr et al 2019). SeisSol is verified with a wide range of community benchmarks, including dipping and branching fault geometries, laboratory derived friction laws, as well as heterogeneous on-fault initial stresses and material properties (de la Puente et al 2009;Pelties et al 2012Pelties et al , 2013Pelties et al , 2014Wollherr et al 2018) in line with the SCEC/USGS Dynamic Rupture Code Verification exercises (Harris et al 2011(Harris et al , 2018.…”
Section: Earthquake-tsunami Coupled Modelingmentioning
confidence: 93%
“…We fit a series of functional regression models that address the following question: what is the epidemiology of activity patterns with age in the UK Biobank and how does disentangling horizontal and vertical variability via registration amplify or modify these trends? We choose to model these associations flexibly using techniques from generalized function-on-scalar regression (FoSR) [ 28 , 29 ], where we allow for the association between the outcome to vary smoothly in time of day, t , and age on the linear predictor scale. We fit separate models for: , , and stratified by sex where are the participant-specific estimated warping functions obtained from the registration algorithm described in Section 2.2 .…”
Section: Methodsmentioning
confidence: 99%
“…Compared to scalar regression, this has the advantage that the temporal correlation structure per dog is automatically incorporated in the model and a time effect does not have to be explicitly specified. An introduction to this model class, including a functional response and scalar influence variables, can be found in Bauer, Scheipl, Küchenhoff, and Gabriel ().…”
Section: Animals Materials and Methodsmentioning
confidence: 99%
“…Pairwise, group differences regarding the serum concentrations were visualised using the effect estimates from the functional regression model. In addition, bootstrap‐based pointwise 95% confidence intervals were estimated for each difference to show the corresponding estimation uncertainties (see Bauer et al., , 4.1). As we did not account for multiple testing, the focus was on interpreting the overall structure of the differences.…”
Section: Animals Materials and Methodsmentioning
confidence: 99%