The supplemental content of this study is categorized into four folders according to type: code, figures, data, and log. Data is first generated based on the code throughout the simulation analysis and stored in the data folder. During the generation process, a log file is created and saved in the log folder to record any issues that may arise, allowing for monitoring of the computer analysis progress through background jobs. Subsequently, the stored data is visualized using plotting functions.
Note: please create the folders (figures, data, and log) before you run the code.
This repository contains the code necessary to simulate and visualize "The generalized Robbins-Monro process and its application to psychophysical experiments for threshold estimation." If you need to use any functions, please first run source("code/Requiredpkg.R") to ensure the necessary packages are downloaded and installed successfully. The settings related to the simulation in the code folder are primarily contained in Hyper_parameter.R, which includes the default parameter settings for the experiment. If changes are needed during the process, updating the code at the beginning of the script before starting the simulation is recommended to ensure the parameters are assigned adequately. The files related to the simulation include Response.R, Methods.R, and Data_and_SE.R. The function in Response.R generates responses based on some assumptions from the literature. Methods.R contains the adaptive method code called Response.R to generate the adaptive method based on the responses. Finally, Data_and_SE.R includes the code necessary to create simulated data and its Monte Carlo Standard Error (SE) based on parameter requirements.
Additionally, we provide example scripts for data generation and visualization: Data_generation.R and Plot.R.
Details can be found within the code content.
If you have any questions or issues regarding the research, please get in touch with us via GitHub (https://github.com/Hardy1Yang/) or email (d11227103@ntu.edu.tw).