impute_fpca {mxfda} | R Documentation |
impute_fpca
Description
Internal function called by TITLE: regression function
that imputes missing data in functional predictors using FPCA.
Usage
impute_fpca(
mxfundata,
id,
r = "r",
value = "fundiff",
knots = NULL,
analysis_vars,
smooth
)
Arguments
mxfundata |
Dataframe of spatial summary functions from multiplex imaging data, in long format. Can be estimated using the function |
id |
Character string, the name of the variable that identifies each unique subject. |
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. |
analysis_vars |
Optional list of variables to be retained for downstream analysis. |
smooth |
Option to smooth data using FPCA. |
Value
A dataframe
where the missing function values (NA) for the value
variable have been replaced with estimates from FPCA.
Author(s)
Julia Wrobel julia.wrobel@emory.edu
Examples
# simulate data
set.seed(1001)