impute_fpca: impute_fpca

In mxfda: A Functional Data Analysis Package for Spatial Single Cell Data

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 extract_summary_functions or provided separately.
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 [e-mail]

Examples

# simulate data
set.seed(1001)

mxfda documentation built on April 3, 2025, 10:25 p.m.