DFFSS: DFFSS scan procedure

In HDSpatialScan: Multivariate and Functional Spatial Scan Statistics

DFFSS scan procedure

Description

This function computes the DFFSS (Distribution-Free Functional scan statistic).

Usage

DFFSS(
  data,
  MC = 999,
  typeI = 0.05,
  nbCPU = 1,
  times = NULL,
  initialization,
  permutations
)

Arguments

data	matrix. Matrix of the data, the rows correspond to the sites (or to the individuals if the observations are by individuals and not by sites) and each column represents an observation time. The times must be the same for each site/individual.
MC	numeric. Number of Monte-Carlo permutations to evaluate the statistical significance of the clusters. By default: 999.
typeI	numeric. The desired type I error. A cluster will be evaluated as significant if its associated p-value is less than typeI. By default 0.05.
nbCPU	numeric. Number of CPU. If nbCPU > 1 parallelization is done. By default: 1.
times	numeric. Times of observation of the data. By default NULL.
initialization	list. Initialization for the scan procedure (see InitScan for more details).
permutations	matrix. Indices of permutations of the data.

Value

An object of class ResScanOutputUniFunct.

References

Camille Frévent and Mohamed-Salem Ahmed and Matthieu Marbac and Michaël Genin (2021). Detecting Spatial Clusters in Functional Data: New Scan Statistic Approaches. Spatial Statistics, 46.

HDSpatialScan documentation built on May 31, 2023, 7:52 p.m.