compound_invariance_pwf: The compound invariance probability weighting function.

In gary-au/pt: Computational models for prospect theory and other theories of risky decision making

Description

The compound invariance probability weighting function is given by

w(p) = (exp(-beta * (-log(x))^alpha)),

where p is the probability constrained by

w(0) = 0, w(1) = 1, 0 < p < 1,

and the two parameters alpha and beta are constrained by

alpha > 0, beta > 0.

Usage

compound_invariance_pwf(par, p)

Arguments

par	vector, contains the alpha and beta parameters for the pwf
p	numeric, the probability

References

Prelec, D. (1998). The probability weighting function. Econometrica, 60(3), 497-528.

al-Nowaihi, A., & Dhami, S. (2006). A simple derivation of Prelec's probability weighting function. Journal of Mathematical Psychology, 50(6), 521-524.

p. 179, 207, Wakker, P. P. (2010). Prospect theory: For risk and ambiguity. Cambridge, UK: Cambridge University Press.

See Also

plotProbW, plotTwoParProbWFam

gary-au/pt documentation built on May 16, 2019, 5:41 p.m.