quanteda.core: Quantitative Analysis of Textual Data

This is an underlying function for textstat_dist and textstat_simil but returns TsparseMatrix.

textstat_proxy(
  x,
  y = NULL,
  margin = c("documents", "features"),
  method = c("cosine", "correlation", "jaccard", "ejaccard", "dice", "edice", "hamman",
    "simple matching", "euclidean", "chisquared", "hamming", "kullback", "manhattan",
    "maximum", "canberra", "minkowski"),
  p = 2,
  min_proxy = NULL,
  rank = NULL,
  use_na = FALSE
)

`x`	a dfm objects; `y` is an optional target matrix matching `x` in the margin on which the similarity or distance will be computed.
`y`	if a dfm object is provided, proximity between documents or features in `x` and `y` is computed.
`margin`	identifies the margin of the dfm on which similarity or difference will be computed: `"documents"` for documents or `"features"` for word/term features.
`method`	character; the method identifying the similarity or distance measure to be used; see Details.
`p`	The power of the Minkowski distance.
`min_proxy`	the minimum proximity value to be recoded.
`rank`	an integer value specifying top-n most proximity values to be recorded.
`use_na`	if `TRUE`, return `NA` for proximity to empty vectors. Note that use of `NA` makes the proximity matrices denser.