Perform kmeans of a dataset using just data in selected columns, then return matrices of all columns

Usage

kmeans_by_selected_cols(
  l,
  cols = NULL,
  log = TRUE,
  base = 2,
  sig_only = TRUE,
  sig_level = 0.05,
  metric = "bootstrap_t_p_val",
  k = NA,
  nstart = 25,
  itermax = 1000
)

Arguments

l: list of results, usually from `compare_many()`
cols: names of columns to perform the k-means with
log: whether to log the data
base: base used in logging (default = 2)
sig_only: return only rows with 1 or more values significant at `sig_level` of `metric`
sig_level: significance level cutoff
metric: the test metric used to determine significance one of: `bootstrap_t_p_val`, `bootstrap_t_fdr` `wilcoxon_p_val`, `wilcoxon_fdr` `kruskal_p_val`, `kruskal_fdr` `rank_prod_p1_p_val`, `rank_prod_p2_p_val`, `rank_prod_p1_fdr`, `rank_prod_p2_fdr`.
k: number of clusters to make
nstart: nstart value for `kmeans()`
itermax: number of `kmeans()` iterations (1000)

Value

list of matrices