Computes predicted choice proportions using the SiGN (Signals for Good News) model, based on input parameters describing reinforcement schedules, stimulus durations, and signalling conditions.
Arguments
- params
A named list of model parameters, typically created with
choice_params(). This list must include all required values such as initial and terminal link durations, terminal link entry and reinforcement probabilities, schedule types. Seechoice_params()for a complete description of required elements.
Value
An object of class "SiGN", which includes:
cp: A numeric vector of predicted choice proportions.details: A data frame containing intermediate model components such as reinforcement rates, delay reductions, beta values, and signalling status.
References
Dunn, R. M., Pisklak, J. M., McDevitt, M. A., & Spetch, M. L. (2024). Suboptimal choice: A review and quantification of the signal for good news (SiGN) model. Psychological Review. 131(1), 58-78. https://doi.org/10.1037/rev0000416
Examples
# Standard FR 1 Initial Links
params <- choice_params(profile = "zentall")
result <- SiGN(params)
result$cp # predicted choice proportion
#> [1] 0.9590059
result$details # access intermediate terms
#> cp r_a r_b r_a_com r_b_com Big_T cr_a cr_b
#> 1 0.9590059 0.05263158 0.04545455 NA NA 21.14286 11.54496 0.5714286
#> dr_avg_a dr_avg_b dr_bonus_a dr_bonus_b beta_a beta_b sig_a sig_b tr_p_a
#> 1 1.428571 0.5714286 9.714286 0 1.041393 1 TRUE FALSE 0.2
#> tr_p_b s_delta beta_log
#> 1 0.5 1 10
# Long VI 30 Initial Links
params <- choice_params(profile = "zentall",
il_dur_a = 30, il_dur_b = 30, il_sched_a = "VI", il_sched_b = "VI")
result <- SiGN(params)
result$cp
#> [1] 0.3070095
result$details
#> cp r_a r_b r_a_com r_b_com Big_T cr_a cr_b
#> 1 0.3070095 0.006097561 0.0125 0.01123596 0.02 61.14286 18.68283 20.57143
#> dr_avg_a dr_avg_b dr_bonus_a dr_bonus_b beta_a beta_b sig_a sig_b tr_p_a
#> 1 9.428571 20.57143 41.71429 0 0.2218487 1 TRUE FALSE 0.2
#> tr_p_b s_delta beta_log
#> 1 0.5 1 10