Description Usage Arguments Author(s) References

Fitting function for function-on-scalar regression for cross-sectional data. This function estimates model parameters using GLS: first, an OLS estimate of spline coefficients is estimated; second, the residual covariance is estimated using an FPC decomposition of the OLS residual curves; finally, a GLS estimate of spline coefficients is estimated. Although this is in the 'BayesFoSR' package, there is nothing Bayesian about this FoSR.

1 2 3 4 5 6 7 8 9 |

`formula` |
a formula indicating the structure of the proposed model. |

`data` |
an optional data frame, list or environment containing the variables in the model. If not found in data, the variables are taken from environment(formula), typically the environment from which the function is called. |

`Kt` |
number of spline basis functions used to estimate coefficient functions |

`basis` |
basis type; options are "bs" for b-splines and "pbs" for periodic b-splines |

`sigma` |
optional covariance matrix used in GLS; if |

`verbose` |
logical defaulting to |

`CI.type` |
Indicates CI type for coefficient functions; options are "pointwise" and "simultaneous" |

Jeff Goldsmith ajg2202@cumc.columbia.edu

Goldsmith, J., Kitago, T. (2016).
Assessing Systematic Effects of Stroke on Motor Control using Hierarchical
Function-on-Scalar Regression. *Journal of the Royal Statistical Society:
Series C*, 65 215-236.

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