run_mfpca function

run_fpca

This is a wrapper for the function mfpca.face from the refund package. EXPAND

run_mfpca(
  mxFDAobject,
  metric = "uni k",
  r = "r",
  value = "fundiff",
  knots = NULL,
  lightweight = FALSE,
  ...
)

Arguments

• mxFDAobject: object of class mxFDA created by make_mxfda() with metrics derived with extract_summary_functions()
• metric: name of calculated spatial metric to use
• r: Character string, the name of the variable that identifies the function domain (usually a radius for spatial summary functions). Default is "r".
• value: Character string, the name of the variable that identifies the spatial summary function values. Default is "fundiff".
• knots: Number of knots for defining spline basis.Defaults to the number of measurements per function divided by 2.
• lightweight: Default is FALSE. If TRUE, removes Y and Yhat from returned mFPCA object. A good option to select for large datasets.
• ...: Optional other arguments to be passed to mfpca.face

Returns

A mxFDA object with the functional_mpca slot for the respective spatial summary function containing: - mxfundata: The original dataframe of spatial summary functions, with scores from FPCA appended for downstream modeling

• fpc_object: A list of class "fpca" with elements described in the documentation for refund::fpca.face

Details

Examples

#load data
data(lung_FDA)

#run mixed fpca
lung_FDA = run_mfpca(lung_FDA, metric = 'uni g')

References

Xiao, L., Ruppert, D., Zipunnikov, V., and Crainiceanu, C. (2016). Fast covariance estimation for high-dimensional functional data. Statistics and Computing, 26, 409-421. DOI: 10.1007/s11222-014-9485-x.

Author(s)

unknown first.last@domain.extension

Julia Wrobel julia.wrobel@emory.edu

Alex Soupir alex.soupir@moffitt.org