voi: Value of information of Multisensory Stimuli

In nicolemunoz99/multisensory: Predicting the conditions under which multisensory integration is favored

Description

Calculates the value of information for two sequential stimuli based on signal-detection theory and Bayesian inference. See Munoz & Blumstein's "Optimal Integration" (under review at Behavioral Ecology), for derivation and list of assumptions. In Munoz & BLumstein, "b" = predator (PRED) state, "a" = non-threat (NONE) state.

Usage

voi(t.prior.b, t.bb.b, t.bb.a, t.s1, t.u1, t.u2, t.k1, t.k2)

Arguments

t.prior.b	prior probability of the world in state "b".
t.bb.b	benefit of correct behavior when world is in state "b".
t.bb.a	benefit of correct behavior when world is in state "a".
t.s1	magnitude of the first stimulus.
t.u1	uncertainty of the 1st stimulus (proportion of overlap of distributions of 1st stimulus).
t.u2	uncertainty of the 2nd stimulus (proportion of overlap of distributions of 2nd stimulus).
t.k1	cost of attending to the 1st stimulus.
t.k2	cost of attending to the 2nd stimulus.

Value

List having components int1, vi1, int2, vi2, st.use

int1: T/F (was the 1st stimulus used?).

vi1: Value of Information of 1st stimulus.

int2: T/F (was the 2nd stimulus used?).

vi2: Value of Information of the 2nd stimulus.

st.use: 0 - neither stimulus used; 1 - only 1st stimulus used; 2 - only 2nd stimulus used; 3 - both stimuli used.

Examples

voi(0.3, 2, 1, -1, 0.2, 0.8, 0, 1)

nicolemunoz99/multisensory documentation built on June 29, 2019, 2:51 p.m.