davids_steepness: David's scores and steepness with Bayesian flavor

In EloSteepness: Bayesian Dominance Hierarchy Steepness via Elo Rating and David's Scores

David's scores and steepness with Bayesian flavor

Description

David's scores and steepness with Bayesian flavor

Usage

davids_steepness(mat, silent = FALSE, ...)

Arguments

mat	square interaction matrix
silent	logical, suppress warnings (default is FALSE)
...	additional arguments for sampling()

Value

a list with results of the modelling fitting, containing the following list items:

steepness

a one-column matrix with the posterior samples for steepness. Each row is one iteration.

norm_ds

an matrix with posterior normalized David's scores for each individual. Each column is one individual. Each row is one iteration.

ids

a character vector with individual ID codes as supplied in mat

diagnostics

a list with information regarding sampling problems

stanfit

the actual stanfit object

mat

the input matrix

Examples

data(dommats, package = "EloRating")
res <- davids_steepness(dommats$elephants, refresh = 0)
plot_steepness(res)

EloSteepness documentation built on Sept. 21, 2023, 1:06 a.m.