cluster.search: Search for putative clusters

In joheli/yea13: Identification of Putative Clusters in Surveillance Data According to Algorithm by Ypma et al. 2013

Description

This function takes a data.frame of one species (or other sensible taxonomic unit) containing information on time, unit, and type and searches for putative clusters.

Usage

cluster.search(d, e, tc, ic, uc, p.n, hs, ...)

Arguments

d	A data.frame containing columns for id, time, unit (e.g. ward) and type (represented by remaining columns).
e	A quadratic matrix with identical row and column names representing effective distances of units contained in d.
tc	A character or numeric identifying name or number, respectively, of time column in d.
ic	A character or numeric identifying name or number, respectively, of id column in d.
uc	A character or numeric identifying name or number, respectively, of unit column in d.
p.n	An integer specifying number of permutations performed.
hs	An integer containing the heights at which trees from hierarchical clustering should be cut.
...	Arguments passed to ypma.diss

Value

A data.frame containing information on putative clusters.

Examples

# starts a cluster search with 100 ('p.n' = 100) permutations (careful: takes a long time!)
test <- cluster.search(s_aureus, e = units_effdist, tc = "time", uc = "unit", ic = "id", p.n = 100, hs = c(2,3,6), dfun = "dist", dfun.args = list(method = "manhattan"))

joheli/yea13 documentation built on Sept. 18, 2020, 11:21 p.m.