vimes: VIsualisation and Monitoring of EpidemicS

In reconhub/vimes: VIsualisation and Monitoring of EpidemicS

Description

The function vimes is used to identify clusters of related cases based on multiple data.

Usage

vimes(x, method = c("basic"), cutoff = NULL, log_dens = NULL,
  graph_opt = vimes_graph_opt(), ...)

Arguments

x	a list of the class 'vimes_data' as returned by vimes_data.
method	a character string indicating the pruning method to be used; see details.
cutoff	a vector with the same length as 'x' indicating cutoff distances beyond which individuals will not be connected in the separate graphs; recycled if needed. If NULL, interactive mode will be triggered to ask the user for cutoff distances.
log_dens	a list of log-density functions to be used for ML estimation; one function is needed for each type of data.
graph_opt	a list of graphical options for the graphs, as returned by vimes_graph_opt.
...	further arguments to be passed to hist.

Details

!!! This package is still under development. Do not use it without contacting the author. !!!

Different methods can be used for graph pruning:

basic

pre-defined cutoffs are used if provided as cutoff; if missing, they are chosen interactively by the user by examining the distribution of distances

Author(s)

Thibaut Jombart [e-mail]

See Also

vimes_data

to prepare the input data.

vimes_prune

for getting individual pruned graphs.

Examples

 ## generate data
 set.seed(2)
 dat1 <- rnorm(30, c(0,1,6))
 dat2 <- rnorm(30, c(0,0,1))
 dat3 <- rnorm(30, c(8,1,2))
 x <- lapply(list(dat1, dat2, dat3), dist)
 x <- vimes_data(x)
 plot(x)

 ## analyse data
 res <- vimes(x, cutoff=c(2,4,2))
 res
 plot(res$graph)

reconhub/vimes documentation built on May 27, 2019, 4:03 a.m.