mds {radiant.multivariate}

(Dis)similarity based brand maps (MDS)

Description

(Dis)similarity based brand maps (MDS)

Usage

mds(
  dataset,
  id1,
  id2,
  dis,
  method = "metric",
  nr_dim = 2,
  seed = 1234,
  data_filter = "",
  envir = parent.frame()
)

Arguments

dataset

Dataset

id1

A character variable or factor with unique entries

id2

A character variable or factor with unique entries

dis

A numeric measure of brand dissimilarity

method

Apply metric or non-metric MDS

nr_dim

Number of dimensions

seed

Random seed

data_filter

Expression entered in, e.g., Data > View to filter the dataset in Radiant. The expression should be a string (e.g., "price > 10000")

envir

Environment to extract data from

Details

See https://radiant-rstats.github.io/docs/multivariate/mds.html for an example in Radiant

Value

A list of all variables defined in the function as an object of class mds

See Also

summary.mds to summarize results

plot.mds to plot results

Examples

mds(city, "from", "to", "distance") %>% str()
mds(diamonds, "clarity", "cut", "price") %>% str()