find.cluster {multivariance} | R Documentation |
Performs the detection of dependence structures algorithm until a cluster is found. This function is the basic building block dependence.structure
. Advanced users, might use it directly.
find.cluster(x, vec = 1:ncol(x), list.cdm = cdms(x, vec = vec), mem = as.numeric(1:max(vec)), cluster.to.vertex = 1:max(mem), vertex.to.cdm = 1:max(mem), previous.n.o.cdms = rep(0, max(mem)), all.multivariances = numeric(0), g = igraph::add.vertices(igraph::graph.empty(, directed = FALSE), max(mem), label = sapply(1:max(mem), function(r) paste(colnames(x, do.NULL = FALSE, prefix = "")[vec == r], collapse = ",")), shape = "circle"), fixed.rejection.level = NA, alpha = 0.05, p.adjust.method = "holm", verbose = TRUE, kvec = 2:max(mem), parameter.range = NULL, type = "conservative", stop.too.many = NULL, ...)
x |
matrix with the samples |
vec |
vector, it indicates which columns are initially treated together as one sample |
list.cdm |
list of centered distance matrices |
mem |
numeric vector, its length is the number of vertices, its content is the number of the corresponding cluster for the current iteration, i.e., vertex |
cluster.to.vertex |
vector, contains the cluster to vertex relations, i.e., |
vertex.to.cdm |
vector, contains the vertex to centered distance matrix relations, i.e., |
previous.n.o.cdms |
vector, number of centered distance matrices in the previous iteration (it is used to ensure that previously check tuples are not checked again) |
all.multivariances |
vector, which contains all distance multivariances which have been calculated so far. Only used to finally return all distance multivariances which have been calculated. |
g |
dependence structure graph |
fixed.rejection.level |
vector, if not |
alpha |
numeric, significance level used for the (distribution-free) tests |
p.adjust.method |
name of the method used to adjust the p-values for multiple testing, see |
verbose |
boolean, if |
kvec |
vector, k-tuples are only checked for each k in |
parameter.range |
numeric matrix, which hosts the range of significance levels or ' |
type |
the method for the detection, one of ' |
stop.too.many |
numeric, upper limit for the number of tested tuples. A warning is issued if it is used. Use |
... |
are passed to |
For further details see dependence.structure
.