approx_rank_expected: Approximation of expected ranks

In netrankr: Analyzing Partial Rankings in Networks

Approximation of expected ranks

Description

Implements a variety of functions to approximate expected ranks for partial rankings.

Usage

approx_rank_expected(P, method = "lpom")

Arguments

P	A partial ranking as matrix object calculated with neighborhood_inclusion or positional_dominance.
method	String indicating which method to be used. see Details.

Details

The method parameter can be set to

lpom

local partial order model

glpom

extension of the local partial order model.

loof1

based on a connection with relative rank probabilities.

loof2

extension of the previous method.

Which of the above methods performs best depends on the structure and size of the partial ranking. See vignette("benchmarks",package="netrankr") for more details.

Value

A vector containing approximated expected ranks.

Author(s)

David Schoch

References

Brüggemann R., Simon, U., and Mey,S, 2005. Estimation of averaged ranks by extended local partial order models. MATCH Commun. Math. Comput. Chem., 54:489-518.

Brüggemann, R. and Carlsen, L., 2011. An improved estimation of averaged ranks of partial orders. MATCH Commun. Math. Comput. Chem., 65(2):383-414.

De Loof, L., De Baets, B., and De Meyer, H., 2011. Approximation of Average Ranks in Posets. MATCH Commun. Math. Comput. Chem., 66:219-229.

See Also

approx_rank_relative, exact_rank_prob, mcmc_rank_prob

Examples

P <- matrix(c(0, 0, 1, 1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 1, rep(0, 10)), 5, 5, byrow = TRUE)
# Exact result
exact_rank_prob(P)$expected.rank

approx_rank_expected(P, method = "lpom")
approx_rank_expected(P, method = "glpom")

netrankr documentation built on Aug. 20, 2023, 5:06 p.m.