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

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.

Value

A vector containing approximated expected ranks.

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.

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
#> V1 V2 V3 V4 V5 #> 1.333 2.111 2.889 4.222 4.444
approx_rank_expected(P,method = 'lpom')
#> [1] 1.2 2.0 3.0 4.5 4.5
approx_rank_expected(P,method = 'glpom')
#> [1] 1.250 2.167 2.833 4.333 4.417