elo.model1: Optimize k parameter in Elo rating method

Description Usage Arguments Examples

View source: R/elo.model1.R

Description

Function to optimize k parameter in Elo Rating Method

Usage

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elo.model1(par, burn_in=100, init_elo = 1000, IA_data, all_ids, p_function = "sigmoid", 
  return_likelihood = T)

Arguments

par

initial value of log(k)

burn_in

burn in period for establishing initial elo scores. Defaults to 100

init_elo

Initial Elo score for all individuals. Defaults to 1000

IA_data

Data frame with Date, Winner, and Loser

all_ids

list of all IDs in sample

p_function

function used to calculate probability of winning. Defaults to sinusoidal function, but use "pnorm" to use the pnorm-based method implemented in the EloRating package.

return_likelihood

Logical; if TRUE, returns log likelihood based on given par, if FALSE returns agonistic interactions table with elo scores based on given value of par

Examples

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#for internal use

EloOptimized documentation built on May 2, 2019, 10:39 a.m.