highlpoints: Highlight highest similarities per point (highlpoints)
In thectar: Hermeneutic Content Analysis

Description Usage Arguments Details Value See Also Examples

View source: R/Graphs.R

highlpoints draws the highest similarities (per point) into an MDS graph.

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highlpoints(similarity, results, links = 3, col = "black",
  coordinates = FALSE, add = FALSE, xlim = NULL, cex.labels = 0.8,
  main = NULL)

`similarity`	Similarity matrix.
`results`	Results of `smacofSym` or a set of coordinates.
`links`	Number of similarities that should be drawn per point. Default is `3`.
`col`	Color of the points in the graph. Default is `black`.
`coordinates`	If `TRUE`, the input `results` consist of a set of coordinates. Default is `FALSE`.
`add`	If `TRUE`, the points will be added to the existing plot. Default is `FALSE`.
`xlim`	Numeric vector giving the x coordinates range.
`cex.labels`	Numeric value indicating font size of the labels.
`main`	Title of the plot.

This function is applicable to an MDS solution computed with the package 'smacof' (Mair, De Leeuw, Borg, & Groenen) or a set of coordinates. It adds the link highest similarities per point, as indicated by the similarity matrix similarity, to the plot of the respective map. The links belonging to one point are displayed in the same color. If there is more than one similarity on the last rank link, all will be shown. The objects must occur in the same order in the results/ coodinates and the similarity matrix.

Nothing.

smacofSym.

## Calculating an MDS using the package 'smacof' and showing the 3 highest 
## similarities per point
data(SDG_coocurrence)
SDG_coocurrence <- SDG_coocurrence[,-2] # Drop second column
similarities <- simi(SDG_coocurrence, method = "as")
dissimilarities <- 1 - similarities
res <- smacof::smacofSym(dissimilarities, type = "ordinal")
highlpoints(similarities, res, links = 3, 
main = "3 Highest Similarities Per Point")