prospect_value_matrix_extend: Calculate Value Matrix

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

Description

Given both normalized gain and loss matrices, this function calculates the value matrix with the value function from Prospect Theory (Reference[1]). It differs from other functions in this package in that it does not take all parameters into account. Yo need to pre-calculate the matrices. See Details.

Usage

prospect_value_matrix_extend(ngain = NULL, nloss = NULL, alpha = 0.88,
  beta = 0.88, lambda = 2.25)

Arguments

ngain	normalized gain matrix
nloss	normalized loss matrix
alpha	numeric between [0, 1]. Determines the concativity of the value function as given by the value function[1].
beta	numeric between [0, 1]. Determines the convexity of the value function as given by the value function[1]
lambda	lambda > 1. Parameter of loss aversion for the value function as given by the value function[1].

Details

You need to pre-calculate the normalized gain and loss matrices, for example with norm_g_l_matrices and give them as a parameter. This is one of the few functions of this package that do not allow you to give the raw data from your product Configurator, but rather calculate a previous result.

Value

the value matrix

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.

See Also

pvMatrix

Examples

prospect_value_matrix_extend(my_ngain, my_nloss)
prospect_value_matrix_extend(ngain = matrix1, nloss = matrix2, alpha = 0.95)

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