Formats clusters in standardized way, optionally estimating cluster prototypes

Usage

formatClusters(
  clusters = NA,
  p = -1,
  clust_names = NA,
  get_prototypes = FALSE,
  x = NA,
  y = NA,
  R = NA
)

Arguments

clusters: Either an integer vector of a list of integer vectors; each vector should contain the indices of a cluster of features. (If there is only one cluster, clusters can either be a list of length 1 or simply an integer vector.) If clusters is specified then R is ignored.
p: integer or numeric; the numbe of features in x (should match ncol(x), if x is provided)
clust_names: A character vector of the names of the clusters in clusters.
get_prototypes: Logical: if TRUE, will identify prototype from each cluster (the feature from each cluster that is most correlated with the response) for the protolasso. In this case, x and y must be provided.
x: n x p numeric matrix; design matrix. Only needs to be provided if get_prototypes is TRUE.
y: Numeric response vector; only needs to be provided if get_prototypes is TRUE. Note: in general, the css function does not require y to be a numeric vector, because the provided fitfun could use a different form of y (for example, a categorical response variable). However, y must be numeric in order to provide prototypes because the prototypes are determined using the correlation between cluster members (columns of x) and y.
R: Numeric p x p matrix; not currently used. Entry ij contains the "substitutive value" of feature i for feature j (diagonal must consist of ones, all entries must be between 0 and 1, and matrix must be symmetric)

Value

A named list with the following elements:

clusters: A named list where each entry is an integer vector of indices of features that are in a common cluster. (The length of list clusters is equal to the number of clusters.) All identified clusters are non-overlapping. All features appear in exactly one cluster (any unclustered features will be put in their own "cluster" of size 1).
multiple: Logical; TRUE if there is more than one cluster of size greater than 1, FALSE otherwise.
prototypes: only returned if get_prototypes=TRUE. An integer vector whose length is equal to the number of clusters. Entry i is the index of the feature belonging to cluster i that is most highly correlated with y (that is, the prototype for the cluster, as in the protolasso; see Reid and Tibshirani 2016).

References

Reid, S., & Tibshirani, R. (2016). Sparse regression and marginal testing using cluster prototypes. Biostatistics, 17(2), 364–376. https://doi.org/10.1093/biostatistics/kxv049.

Author

Gregory Faletto, Jacob Bien