nmds: Non-metric Multidimensional Scaling (NMDS)
In Andros-Spica/cerUB: Protocols for exploring archaeometric data

Apply Non-metric Multidimensional Scaling to a given distance matrix, calculate variable covariances, and the percent of variance explained by 2D and 3D projections.

1 2	nmds(distance_matrix, original_data, variable_tags = c(), dimensions = 2, init_seed = 0, trymax = 100, autotransform = FALSE)

`distance_matrix`	distance or dissimilarity matrix
`original_data`	data frame containing the original data
`variable_tags`	Character, two-column data frame containing (1) the names of variables and (2) their tags.
`dimensions`	Numeric, number of dimensions of the projection equivalent to k in `metaMDS`.
`init_seed`	Numeric, the seed for the random number generator used by `metaMDS`.
`trymax, autotransform`	Numeric, Maximum number of random starts in search of stable solution. Logical, whether to use simple heuristics for possible data transformation of typical community data (see below). If you do not have community data, you should probably set autotransform = FALSE. Arguments passed to `metaMDS`.