ProbWeight: Create an instance of a ProbWeight class.

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

Description

Creates an instance of the ProbWeight class.

Usage

ProbWeight(fun, par)

Arguments

fun	text, the probability function string
par	vector, parameters for the probability function

Details

This function creates an instance of a ProbWeight class. The following functional forms are currently implemented:

linear

Tversky_Kahneman_1992 (requires 1 parameter > 0.28)

linear_in_log_odds (requires 2 parameters)

power (requires 2 parameters)

neo_additive (requires 2 parameters)

hyperbolic_logarithm (requires 2 parameters)

exponential_power (requires 2 parameters)

compound_invariance (requires 2 parameters)

constant_relative_sensitivity (requires 2 parameters)

References

Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5(4), 297-323.

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

Wu, G., & Gonzalez, R. (1996). Curvature of the probability weighting function. Management Science, 42(12), 1676-1690.

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

Stott, H. P. (2006). Cumulative prospect theory's functional menagerie. Journal of Risk and Uncertainty, 32(2), 101-130.

Examples

# This example creates a linear in log odds
# probability weighting function.

linear_in_log_odds_prob_weight <-
	ProbWeight(fun="linear_in_log_odds",
	par=c(alpha=0.61, beta=0.724))

# These examples create the probability weighting functions
# used by Tversky and Kahneman (1992).

tk_1992_positive_prob_weight <-
	ProbWeight(fun="Tversky_Kahneman_1992",
	par=c(alpha=0.61))

tk_1992_negative_prob_weight <-
	ProbWeight(fun="Tversky_Kahneman_1992",
	par=c(alpha=0.69))

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