tests/Test_Birnbaum_Navarette_1998.R
In gary-au/pt: Computational models for prospect theory and other theories of risky decision making
library("pt")
########################
# Birnbaum, M. H., & Navarrete, J. B. (1998). Testing descriptive utility theories: Violations of stochastic dominance and cumulative independence. Journal of Risk and Uncertainty, 17(1), 49-79.
#
# Birnbaum, M. H. (1997). Violations of monotonicity in judgment and decision making. In A. A. J. Marley (Ed.), Choice, decision, and measurement: Essays in honor of R. Duncan Luce (pp. 73-100). Mahwah, NJ: Erlbaum.
# on the violation of stochastic dominance recipe
########################
my_list <- vsdChoices(x=12, y=96, p="0.1", q="0.9", x_plus=14, y_minus=90, r="0.05")
my_list
########################
#
# p.58
#
########################
# G+=(12, 0.05; 14, 0.05; 96, 0.9)
# G-=(12, 0.1; 90, 0.05; 96, 0.85)
#CWU
#CE(G+)=56.99 < CE(G-)=63.23
#PT
#CE(G+)=70.27 > CE(G-)=69.73
choice_ids <- c(1, 1, 1, 1, 1, 1)
gamble_ids <- c(1, 1, 1, 2, 2, 2)
outcome_ids <- c(1, 2, 3, 1, 2, 3)
objective_consequences <- c(12, 14, 96, 12, 90, 96)
probability_strings <-
c("0.05", "0.05", "0.9", "0.1", "0.05", "0.85")
my_choices <- Choices(choice_ids=choice_ids,
gamble_ids=gamble_ids,
outcome_ids=outcome_ids,
objective_consequences=objective_consequences,
probability_strings=probability_strings)
my_choices
my_pwf <-
ProbWeight(fun="power",
par=c(alpha=0.7, beta=1))
delta <- -1
my_utility <- Utility(fun="power",
par=c(alpha=1, beta=1, lambda=1))
compareTAX(my_choices,
prob_weight=my_pwf,
utility=my_utility,
delta=delta,
digits=4)
# cid gid ev tax ce rp
# 1 1 1 87.7 45.77 45.77 41.93
# 2 1 2 87.3 63.1 63.1 24.2
branch_weight_list <- list(
c(0.37, 0.63),
c(0.16, 0.33, 0.51))
my_pwf <-
ProbWeight(fun="power",
par=c(alpha=0.6, beta=1))
my_utility <- Utility(fun="power",
par=c(alpha=1, beta=1, lambda=1))
compareRAM(my_choices,
branch_weight_list=branch_weight_list,
prob_weight=my_pwf,
utility=my_utility,
digits=4)
# cid gid ev ramu ce rp
# 1 1 1 87.7 55.97 55.97 31.73
# 2 1 2 87.3 62.18 62.18 25.12
tk_1992_utility <- Utility(fun="power",
par=c(alpha=0.88, beta=0.88, lambda=2.25))
tk_1992_positive_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.61))
tk_1992_negative_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.69))
comparePT(my_choices,
prob_weight_for_positive_outcomes=tk_1992_positive_probWeight,
prob_weight_for_negative_outcomes=tk_1992_negative_probWeight,
utility=tk_1992_utility, digits=4)
# cid gid ev pt ce rp
# 1 1 1 87.7 42.18 70.27 17.43
# 2 1 2 87.3 41.9 69.73 17.57
########################
#
# p.59
#
########################
# S'''=(40, 0.2; 98, 0.8)
# R'''=(10, 0.1; 98, 0.9)
#CWU
# CE(S''')=73.54 > CE(R''')=70.76
#PT
# CE(S''')=74.52 > CE(R''')=70.72
choice_ids <- c(1, 1, 1, 1)
gamble_ids <- c(1, 1, 2, 2)
outcome_ids <- c(1, 2, 1, 2)
objective_consequences <- c(40, 98, 10, 98)
probability_strings <-
c("0.2", "0.8", "0.1", "0.9")
my_choices <- Choices(choice_ids=choice_ids,
gamble_ids=gamble_ids,
outcome_ids=outcome_ids,
objective_consequences=objective_consequences,
probability_strings=probability_strings)
my_choices
branch_weight_list <- list(
c(0.37, 0.63))
my_pwf <-
ProbWeight(fun="power",
par=c(alpha=0.6, beta=1))
my_utility <- Utility(fun="power",
par=c(alpha=1, beta=1, lambda=1))
compareRAM(my_choices,
branch_weight_list=branch_weight_list,
prob_weight=my_pwf,
utility=my_utility,
digits=4)
tk_1992_utility <- Utility(fun="power",
par=c(alpha=0.88, beta=0.88, lambda=2.25))
tk_1992_positive_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.61))
tk_1992_negative_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.69))
comparePT(my_choices,
prob_weight_for_positive_outcomes=tk_1992_positive_probWeight,
prob_weight_for_negative_outcomes=tk_1992_negative_probWeight,
utility=tk_1992_utility, digits=4)
# cid gid ev pt ce rp
# 1 1 1 86.4 44.42 74.52 11.88
# 2 1 2 89.2 42.42 70.72 18.48
########################
#
# p.72
#
########################
# CWU(12, 0.9; 96, 0.05; 96, 0.05) = 24.18 > CWU(12, 0.9; 96, 0.1) = 23.60
# CWU(12, 0.05; 12, 0.05; 96, 0.9) = 55.6 < CWU(12, 0.1; 96, 0.9) = 70.0
choice_ids <- c(1, 1, 1, 1, 1)
gamble_ids <- c(1, 1, 1, 2, 2)
outcome_ids <- c(1, 2, 3, 1, 2)
objective_consequences <- c(12, 96, 96, 12, 96)
probability_strings <-
c("0.9", "0.05", "0.05", "0.9", "0.1")
my_choices <- Choices(choice_ids=choice_ids,
gamble_ids=gamble_ids,
outcome_ids=outcome_ids,
objective_consequences=objective_consequences,
probability_strings=probability_strings)
my_choices
my_pwf <-
ProbWeight(fun="power",
par=c(alpha=0.7, beta=1))
delta <- -1
my_utility <- Utility(fun="power",
par=c(alpha=1, beta=1, lambda=1))
compareTAX(my_choices,
prob_weight=my_pwf,
utility=my_utility,
delta=delta,
digits=4)
# cid gid ev tax ce rp
# 1 1 1 11.6 13.32 13.32 -1.716
# 2 1 2 9.6 8.962 8.962 0.6384
branch_weight_list <- list(
c(1, 2),
c(1, 2, 3))
my_pwf <-
ProbWeight(fun="power",
par=c(alpha=0.6, beta=1))
my_utility <- Utility(fun="power",
par=c(alpha=1, beta=1, lambda=1))
compareRAM(my_choices,
branch_weight_list=branch_weight_list,
prob_weight=my_pwf,
utility=my_utility,
digits=4)
tk_1992_utility <- Utility(fun="power",
par=c(alpha=0.88, beta=0.88, lambda=2.25))
tk_1992_positive_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.61))
tk_1992_negative_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.69))
comparePT(my_choices,
prob_weight_for_positive_outcomes=tk_1992_positive_probWeight,
prob_weight_for_negative_outcomes=tk_1992_negative_probWeight,
utility=tk_1992_utility, digits=4)
# cid gid ev pt ce rp
# 1 1 1 11.6 12.03 16.89 -5.287
# 2 1 2 9.6 8.06 10.71 -1.114
choice_ids <- c(1, 1, 1, 1, 1)
gamble_ids <- c(1, 1, 1, 2, 2)
outcome_ids <- c(1, 2, 3, 1, 2)
objective_consequences <- c(12, 12, 96, 12, 96)
probability_strings <-
c("0.05", "0.05", "0.9", "0.1", "0.9")
my_choices <- Choices(choice_ids=choice_ids,
gamble_ids=gamble_ids,
outcome_ids=outcome_ids,
objective_consequences=objective_consequences,
probability_strings=probability_strings)
my_choices
my_pwf <-
ProbWeight(fun="power",
par=c(alpha=0.7, beta=1))
delta <- -1
my_utility <- Utility(fun="power",
par=c(alpha=1, beta=1, lambda=1))
compareTAX(my_choices,
prob_weight=my_pwf,
utility=my_utility,
delta=delta,
digits=4)
gary-au/pt documentation built on May 16, 2019, 5:41 p.m.
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library("pt")
########################
# Birnbaum, M. H., & Navarrete, J. B. (1998). Testing descriptive utility theories: Violations of stochastic dominance and cumulative independence. Journal of Risk and Uncertainty, 17(1), 49-79.
#
# Birnbaum, M. H. (1997). Violations of monotonicity in judgment and decision making. In A. A. J. Marley (Ed.), Choice, decision, and measurement: Essays in honor of R. Duncan Luce (pp. 73-100). Mahwah, NJ: Erlbaum.
# on the violation of stochastic dominance recipe
########################
my_list <- vsdChoices(x=12, y=96, p="0.1", q="0.9", x_plus=14, y_minus=90, r="0.05")
my_list
########################
#
# p.58
#
########################
# G+=(12, 0.05; 14, 0.05; 96, 0.9)
# G-=(12, 0.1; 90, 0.05; 96, 0.85)
#CWU
#CE(G+)=56.99 < CE(G-)=63.23
#PT
#CE(G+)=70.27 > CE(G-)=69.73
choice_ids <- c(1, 1, 1, 1, 1, 1)
gamble_ids <- c(1, 1, 1, 2, 2, 2)
outcome_ids <- c(1, 2, 3, 1, 2, 3)
objective_consequences <- c(12, 14, 96, 12, 90, 96)
probability_strings <-
c("0.05", "0.05", "0.9", "0.1", "0.05", "0.85")
my_choices <- Choices(choice_ids=choice_ids,
gamble_ids=gamble_ids,
outcome_ids=outcome_ids,
objective_consequences=objective_consequences,
probability_strings=probability_strings)
my_choices
my_pwf <-
ProbWeight(fun="power",
par=c(alpha=0.7, beta=1))
delta <- -1
my_utility <- Utility(fun="power",
par=c(alpha=1, beta=1, lambda=1))
compareTAX(my_choices,
prob_weight=my_pwf,
utility=my_utility,
delta=delta,
digits=4)
# cid gid ev tax ce rp
# 1 1 1 87.7 45.77 45.77 41.93
# 2 1 2 87.3 63.1 63.1 24.2
branch_weight_list <- list(
c(0.37, 0.63),
c(0.16, 0.33, 0.51))
my_pwf <-
ProbWeight(fun="power",
par=c(alpha=0.6, beta=1))
my_utility <- Utility(fun="power",
par=c(alpha=1, beta=1, lambda=1))
compareRAM(my_choices,
branch_weight_list=branch_weight_list,
prob_weight=my_pwf,
utility=my_utility,
digits=4)
# cid gid ev ramu ce rp
# 1 1 1 87.7 55.97 55.97 31.73
# 2 1 2 87.3 62.18 62.18 25.12
tk_1992_utility <- Utility(fun="power",
par=c(alpha=0.88, beta=0.88, lambda=2.25))
tk_1992_positive_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.61))
tk_1992_negative_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.69))
comparePT(my_choices,
prob_weight_for_positive_outcomes=tk_1992_positive_probWeight,
prob_weight_for_negative_outcomes=tk_1992_negative_probWeight,
utility=tk_1992_utility, digits=4)
# cid gid ev pt ce rp
# 1 1 1 87.7 42.18 70.27 17.43
# 2 1 2 87.3 41.9 69.73 17.57
########################
#
# p.59
#
########################
# S'''=(40, 0.2; 98, 0.8)
# R'''=(10, 0.1; 98, 0.9)
#CWU
# CE(S''')=73.54 > CE(R''')=70.76
#PT
# CE(S''')=74.52 > CE(R''')=70.72
choice_ids <- c(1, 1, 1, 1)
gamble_ids <- c(1, 1, 2, 2)
outcome_ids <- c(1, 2, 1, 2)
objective_consequences <- c(40, 98, 10, 98)
probability_strings <-
c("0.2", "0.8", "0.1", "0.9")
my_choices <- Choices(choice_ids=choice_ids,
gamble_ids=gamble_ids,
outcome_ids=outcome_ids,
objective_consequences=objective_consequences,
probability_strings=probability_strings)
my_choices
branch_weight_list <- list(
c(0.37, 0.63))
my_pwf <-
ProbWeight(fun="power",
par=c(alpha=0.6, beta=1))
my_utility <- Utility(fun="power",
par=c(alpha=1, beta=1, lambda=1))
compareRAM(my_choices,
branch_weight_list=branch_weight_list,
prob_weight=my_pwf,
utility=my_utility,
digits=4)
tk_1992_utility <- Utility(fun="power",
par=c(alpha=0.88, beta=0.88, lambda=2.25))
tk_1992_positive_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.61))
tk_1992_negative_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.69))
comparePT(my_choices,
prob_weight_for_positive_outcomes=tk_1992_positive_probWeight,
prob_weight_for_negative_outcomes=tk_1992_negative_probWeight,
utility=tk_1992_utility, digits=4)
# cid gid ev pt ce rp
# 1 1 1 86.4 44.42 74.52 11.88
# 2 1 2 89.2 42.42 70.72 18.48
########################
#
# p.72
#
########################
# CWU(12, 0.9; 96, 0.05; 96, 0.05) = 24.18 > CWU(12, 0.9; 96, 0.1) = 23.60
# CWU(12, 0.05; 12, 0.05; 96, 0.9) = 55.6 < CWU(12, 0.1; 96, 0.9) = 70.0
choice_ids <- c(1, 1, 1, 1, 1)
gamble_ids <- c(1, 1, 1, 2, 2)
outcome_ids <- c(1, 2, 3, 1, 2)
objective_consequences <- c(12, 96, 96, 12, 96)
probability_strings <-
c("0.9", "0.05", "0.05", "0.9", "0.1")
my_choices <- Choices(choice_ids=choice_ids,
gamble_ids=gamble_ids,
outcome_ids=outcome_ids,
objective_consequences=objective_consequences,
probability_strings=probability_strings)
my_choices
my_pwf <-
ProbWeight(fun="power",
par=c(alpha=0.7, beta=1))
delta <- -1
my_utility <- Utility(fun="power",
par=c(alpha=1, beta=1, lambda=1))
compareTAX(my_choices,
prob_weight=my_pwf,
utility=my_utility,
delta=delta,
digits=4)
# cid gid ev tax ce rp
# 1 1 1 11.6 13.32 13.32 -1.716
# 2 1 2 9.6 8.962 8.962 0.6384
branch_weight_list <- list(
c(1, 2),
c(1, 2, 3))
my_pwf <-
ProbWeight(fun="power",
par=c(alpha=0.6, beta=1))
my_utility <- Utility(fun="power",
par=c(alpha=1, beta=1, lambda=1))
compareRAM(my_choices,
branch_weight_list=branch_weight_list,
prob_weight=my_pwf,
utility=my_utility,
digits=4)
tk_1992_utility <- Utility(fun="power",
par=c(alpha=0.88, beta=0.88, lambda=2.25))
tk_1992_positive_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.61))
tk_1992_negative_probWeight <-
ProbWeight(fun="Tversky_Kahneman_1992",
par=c(alpha=0.69))
comparePT(my_choices,
prob_weight_for_positive_outcomes=tk_1992_positive_probWeight,
prob_weight_for_negative_outcomes=tk_1992_negative_probWeight,
utility=tk_1992_utility, digits=4)
# cid gid ev pt ce rp
# 1 1 1 11.6 12.03 16.89 -5.287
# 2 1 2 9.6 8.06 10.71 -1.114
choice_ids <- c(1, 1, 1, 1, 1)
gamble_ids <- c(1, 1, 1, 2, 2)
outcome_ids <- c(1, 2, 3, 1, 2)
objective_consequences <- c(12, 12, 96, 12, 96)
probability_strings <-
c("0.05", "0.05", "0.9", "0.1", "0.9")
my_choices <- Choices(choice_ids=choice_ids,
gamble_ids=gamble_ids,
outcome_ids=outcome_ids,
objective_consequences=objective_consequences,
probability_strings=probability_strings)
my_choices
my_pwf <-
ProbWeight(fun="power",
par=c(alpha=0.7, beta=1))
delta <- -1
my_utility <- Utility(fun="power",
par=c(alpha=1, beta=1, lambda=1))
compareTAX(my_choices,
prob_weight=my_pwf,
utility=my_utility,
delta=delta,
digits=4)
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