extract_summary_functions {mxfda}

Extract Summary Functions

Description

Function to extract spatial summary functions from the Spatial slot of an mxFDA object

Usage

extract_summary_functions(
  mxFDAobject,
  r_vec = seq(0, 100, by = 10),
  extract_func = c(univariate, bivariate),
  summary_func = c(Kest, Lest, Gest),
  markvar,
  mark1,
  mark2 = NULL,
  edge_correction,
  breaks = NULL
)

Arguments

mxFDAobject

object of class mxFDA

r_vec

Numeric vector of radii over which to evaluate spatial summary functions. Must begin at 0.

extract_func

Defaults to univariate, which calculates univariate spatial summary functions. Choose bivariate for bivariate spatial summary functions.

summary_func

Spatial summary function to calculate. Options are c(Kest, Lest, Gest) which denote Ripley's K, Besag's L, and nearest neighbor G function, respectively.

markvar

The name of the variable that denotes cell type(s) of interest. Character.

mark1

Character string that denotes first cell type of interest.

mark2

Character string that denotes second cell type of interest for calculating bivariate summary statistics. Not used when calculating univariate statistics.

edge_correction

Character string that denotes the edge correction method for spatial summary function. For Kest and Lest choose one of c("border", "isotropic", "Ripley", "translate", "none"). For Gest choose one of c("rs", "km", "han")

breaks

integer value for number of breaks in r_vec. Used only for entropy measure

Details

Value

an object of class mxFDA containing the corresponding spatial summary function slot filled. See make_mxfda() for object structure details.

Author(s)

Julia Wrobel [e-mail]

Alex Soupir [e-mail]

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.

spatstat.explore::Kest()

spatstat.explore::Gest()

spatstat.explore::Lest()

spatstat.explore::Kcross()

spatstat.explore::Gcross()

spatstat.explore::Lcross()

Examples

#load ovarian FDA object
data('ovarian_FDA')

#run function
ovarian_FDA = extract_summary_functions(ovarian_FDA, r_vec = 0:100,
                                        extract_func = univariate,
                                        summary_func = Kest,
                                        markvar = "immune",
                                        mark1 = "immune",
                                        edge_correction = "trans")