ecov_big: Estimate Basic Covariance Elements

View source: R/ecov_big.R

ecov_bigR Documentation

Estimate Basic Covariance Elements

Description

Compute all possible products of effects for all features from weighted ESJT data, wFFdata. Note that the average of the dAdB elements will ultimately equal the covariances forming the expectancy matrix used to estimate functional field models. Note that this action can be particularly useful when there is a SINGLE action (or TWO MAIN actions) that are being considered for a given scenario (such as 'Cooperate vs. Defect?' in a "Prisoner's Dilemma" situation; or 'Go straight vs. Swerve?' in a "Chicken" situation). If there are MORE than two actions being represented for a single situation, you may want to use the ecov_long function instead.

Note: data can be weighted using sweighteddata function

Usage

ecov_big(wFFdata, P_ID = "P_ID", S_ID = "S_ID")

Arguments

wFFdata

weighted functional field data

Details

Usage notes: FFdata should have format of P_ID, S_ID, Did_A, as first three columns, followed by effect ratings, and end in Likelihood

Value

Effect covariance matrix


Dustin-Wood/funfield documentation built on July 20, 2023, 7:10 a.m.