pvalue_fun: Implements prospect theory's value function

In avilesd/productConfig: Tools to analyze behavioral patterns from Product Configurators

Description

Given gains and losses relative to a reference points, we use prospect theory's value function to calculate the value matrix[1]. We use default values for the parameters of diminishing sensitity and loss aversion, but this can be inputed differently. Calculates the value function for one value at a time. The function is used to calculate the value matrix [2] in pvMatrix.

Usage

pvalue_fun(ngain_ij, nloss_ij, alpha = 0.88, beta = 0.88, lambda = 2.25)

Arguments

ngain_ij	gain value corresponding to a specific attribute (j) and round (i)
nloss_ij	loss value corresponding to the same specific attribute and round as ngain_ij
alpha	parameter for diminishing sensitivity in the gain domain. Default value = 0.88. Usual values are in the (0,1) interval.
beta	parameter for diminishing sensitivity in the loss domain. Default value = 0.88. Usual values are in the (0,1) interval.
lambda	parameter for loss aversion. Default value = 2.25. Values for lambda should be > 1.

Value

the output of the value function [1]

References

[1] Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica: Journal of the Econometric Society, 263-291.

[2] Fan, Z. P., Zhang, X., Chen, F. D., & Liu, Y. (2013). Multiple attribute decision making considering aspiration-levels: A method based on prospect theory. Computers & Industrial Engineering, 65(2), 341-350.

Examples

pvalue_fun(3, 0)
pvalue_fun(0, -1.5, alpha =0.75, lambda=3)

avilesd/productConfig documentation built on May 11, 2019, 4:08 p.m.