ExpectedUtility

ExpectedUtility constructs a model object for expected utility theory

• α: utility curvature for gains

Constructor

ExpectedUtility(;α=.80)

Gamble

Gamble constructs a gamble object with probability vector p and outcome vector v.

• p: probability vector
• v: outcome vector

Constructor

Gamble(;p=[.5,.5], v=[10.0,0.0])

ProspectTheory

ProspectTheory constructs a model object for cummulative prospect theory. By default, parameters for utility curvature and probability weigting are equal gains and losses.

• α: utility curvature for gains
• β: utility curvature for losses
• γg: probability weighting parameter for gains
• γl: probability weighting parameter for losses
• λ: loss aversion parameter

Constructor

ProspectTheory(;α=.80, β=α, γg=.70, γl=γg, λ=2.25)

References

Fennema, H., & Wakker, P. (1997). Original and cumulative prospect theory: A discussion of empirical differences. Journal of Behavioral Decision Making, 10(1), 53-64.

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

TAX

TAX constructs a model object for transfer of attention exchange.

• δ: transfer of attention parameter
• γ: probability weighting parameter
• β: utility curvature

Constructor

TAX(;δ=.80, β=.3, γ=.70)

References

Birnbaum, M. H., & Chavez, A. (1997). Tests of theories of decision making: Violations of branch independence and distribution independence. Organizational Behavior and human decision Processes, 71(2), 161-194. Birnbaum, M. H. (2008). New paradoxes of risky decision making. Psychological review, 115(2), 463.

UtilityModel

UtilityModel is an abstract utility-based model object ````

mean

mean a method for computing the mean for the TAX model

• model: a model M <: UtilityModel
• gamble: a gamble object

Function Signature

mean(model::TAX, gamble::Gamble)

mean

mean generic method for computing mean

• model: a model M <: UtilityModel
• gamble: a gamble object

Function Signature

mean(model::UtilityModel, gamble::Gamble)

std

std a generic method for computing the standard deviation of the gamble

• model: a model M <: UtilityModel
• gamble: a gamble object

Function Signature

std(model::UtilityModel, gamble::Gamble)

var

var a generic method for computing the variance of the gamble

• model: a model M <: UtilityModel
• gamble: a gamble object

Function Signature

var(model::UtilityModel, gamble::Gamble)

computeweights

_compute_weights computes decision weights based on cummulative outcomes

• p: a probability vector
• γ: parameter that controls weighting of low and high probabilities

Function Signature

_compute_weights(p, γ)

compute_utility

compute_utility computes utility of gamble outcomes according to expected utility theory

• model: a model object for prospect theory
• gamble: a gamble object

Function Signature

compute_utility(model::ExpectedUtility, gamble::Gamble)

compute_utility

compute_utility computes utility of gamble outcomes according to prospect theory

• model: a model object for prospect theory
• gamble: a gamble object

Function Signature

compute_utility(model::ProspectTheory, gamble::Gamble)

compute_utility

compute_utility computes utility of gamble outcomes according to TAX

• model: a model object for TAX
• gamble: a gamble object

Function Signature

compute_utility(model::TAX, gamble::Gamble)

compute_weights

compute_weights computes decision weights based on cummulative outcomes

• model: a model object for prospect theory
• gamble: a gamble object

Function Signature

compute_weights(model::ProspectTheory, gamble::Gamble)

compute_weights

compute_weights a generic method for computing decision weights

• model: a model M <: UtilityModel
• gamble: a gamble object

Function Signature

compute_weights(model::UtilityModel, gamble::Gamble)

sort!

sort! a generic method for sorting gamble probabilities and values. The generic method does not sort the gambles

• model: a model M <: UtilityModel
• gamble: a gamble object

Function Signature

sort!(model::UtilityModel, gamble)