mcmc_rank_prob  R Documentation 
Performs a probabilistic rank analysis based on an almost uniform sample of possible rankings that preserve a partial ranking.
mcmc_rank_prob(P, rp = nrow(P)^3)
P 
P A partial ranking as matrix object calculated with neighborhood_inclusion or positional_dominance. 
rp 
Integer indicating the number of samples to be drawn. 
This function can be used instead of exact_rank_prob
if the number of elements in P
is too large for an exact computation. As a rule of thumb,
the number of samples should be at least cubic in the number of elements in P
.
See vignette("benchmarks",package="netrankr")
for guidelines and benchmark results.
expected.rank 
Estimated expected ranks of nodes 
relative.rank 
Matrix containing estimated relative rank probabilities:

David Schoch
Bubley, R. and Dyer, M., 1999. Faster random generation of linear extensions. Discrete Mathematics, 201(1):8188
exact_rank_prob, approx_rank_relative, approx_rank_expected
## Not run: data("florentine_m") P < neighborhood_inclusion(florentine_m) res < exact_rank_prob(P) mcmc < mcmc_rank_prob(P, rp = vcount(g)^3) # mean absolute error (expected ranks) mean(abs(res$expected.rank  mcmc$expected.rank)) ## End(Not run)
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