perm2decomp

Given a permutation and a distance name generate the decomposition vector

Includes functions to work with the Mallows and Generalized Mallows
Models. The considered distances are Kendall's-tau, Cayley, Hamming and Ulam
and it includes functions for making inference, sampling and learning such
distributions, some of which are novel in the literature. As a by-product,
PerMallows also includes operations for permutations, paying special attention
to those related with the Kendall's-tau, Cayley, Ulam and Hamming distances. It
is also possible to generate random permutations at a given distance, or with
a given number of inversions, or cycles, or fixed points or even with a given
length on LIS (longest increasing subsequence).

Ekhine Irurozki

PerMallows

Permutations and Mallows Distributions

Borja Calvo

perm2decomp function

<dl><dt>perm</dt>
<dd>the permutation</dd>
<dt>dist.name</dt>
<dd>optional the name of the distance. One of: kendall (default), cayley, hamming</dd></dl>

Arguments

Get the decomposition vector — perm2decomp

<dl>

<dt>perm</dt>
<dd>the permutation</dd>


<dt>dist.name</dt>
<dd>optional the name of the distance. One of: kendall (default), cayley, hamming</dd>

</dl>

perm2decomp: Get the decomposition vector

Description

Usage

Value

Arguments

Examples