Description Usage Arguments Details Value Author(s) Examples

`Minstress`

is a heuristic to find better non-metric MDS solutions,
by finding better starting configurations, instead of just using a random one.

1 | ```
Minstress(x, p, s, k, iter = 5, pb = F, m = "euclidean")
``` |

`x` |
a data frame containing numeric values only |

`p` |
the size of the population of seeds (any positive integer) |

`s` |
the number of seeds we sample (any positive integer) |

`k` |
the number of dimensions wanted (any positive integer) |

`iter` |
a positive integer specifying the number of iterations. |

`pb` |
a Boolean variable declaring if one wants to display a pogress bar (default: False) |

`m` |
a string specifying the distance method (default: 'euclidean') |

This function performs several iterations, each using a different starting seed, and in turn each one of those iterations performs non-metric MDS many times (typically, thousands or more) in an attempt to find the best seed (which induces a particular initial configuration) of them all.

A list informing about dimensionality, minimum STRESS level found, and best seed found. One can then use the best seed found to perform non-metric MDS with a better initial configuration (generally).

Albert Dorador

1 2 3 4 5 6 7 8 9 |

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