Description Usage Arguments References See Also
The hyperbolic-logarithm probability weighting function is given by
w(p) = (1 - alpha * log(p))^(-beta/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.
1 |
par |
vector, contains the alpha and beta parameters for the pwf |
p |
numeric, the probability |
Prelec, D. (1998). The probability weighting function. Econometrica, 60(3), 497-528.
p. 176, Luce, R. D. (2001). Reduction invariance and Prelec's weighting functions. Journal of Mathematical Psychology, 45(1), 167-179.
Footnote 3, p. 105, Stott, H. P. (2006). Cumulative prospect theory's functional menagerie. Journal of Risk and Uncertainty, 32(2), 101-130.
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