vb_mult_fpca: Multilevel FoSR using Variational Bayes and FPCA

In jeff-goldsmith/BayesFoSR: Bayesian Function-on-Scalar Regression

Description

Fitting function for function-on-scalar regression for multilevel data. This function estimates model parameters using a VB and estimates the residual covariance surface using FPCA.

Usage

vb_mult_fpca(formula, data = NULL, verbose = TRUE, Kt = 5, Kp = 2,
  alpha = 0.1)

Arguments

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.
verbose	logical defaulting to TRUE – should updates on progress be printed?
Kt	number of spline basis functions used to estimate coefficient functions
Kp	number of FPCA basis functions to be estimated

Author(s)

Jeff Goldsmith [e-mail]

References

Goldsmith, J., Kitago, T. (Under Review). Assessing Systematic Effects of Stroke on Motor Control using Hierarchical Function-on-Scalar Regression.

jeff-goldsmith/BayesFoSR documentation built on May 19, 2019, 1:45 a.m.