ryser: The Ryser method for computing an expected permutation matrix

In expperm: Computing Expectations and Marginal Likelihoods for Permutations

Description

Computes the expected permutation matrix and marginal likelihood from a matrix of assignment likelihoods using the Ryser method.

Usage

ryser(A, return.permanent = FALSE)

Arguments

A	A matrix of assignment likelihoods.
return.permanent	A logical value indicating whether the function should also return the permanent of A, which is then added to the output as an attribute.

Value

E(P), the expected permutation matrix corresponding to A.

Examples

data(A)
ryser(A)

Example output

Attaching package: ‘expperm’

The following object is masked from ‘package:base’:

    sink

            [,1]       [,2]       [,3]         [,4]        [,5]       [,6]
[1,] 0.008233721 0.47259415 0.11714084 0.1703788235 0.004753930 0.06048740
[2,] 0.150689657 0.20364422 0.38485703 0.0137567257 0.005901263 0.23139485
[3,] 0.144996544 0.05417024 0.21618341 0.0612603277 0.400234136 0.06457822
[4,] 0.027018248 0.01052152 0.09781482 0.5606853837 0.149153128 0.13966619
[5,] 0.008849923 0.09552199 0.06456047 0.0920951473 0.050369001 0.21377168
[6,] 0.632440321 0.04124113 0.02171779 0.0003849017 0.042591466 0.11518479
[7,] 0.027771586 0.12230676 0.09772564 0.1014386904 0.346997077 0.17491687
            [,7]
[1,] 0.166411146
[2,] 0.009756256
[3,] 0.058577123
[4,] 0.015140702
[5,] 0.474831789
[6,] 0.146439602
[7,] 0.128843383

expperm documentation built on May 29, 2019, 1:02 a.m.