Soft-Thresholded Varying Coefficient Model

This is the code for the paper "Simultaneous selection and inference for varying coefficients with zero regions: a soft-thresholding approach".

Citation: Yang, Y., Pan, Z., Kang, J., Brummett, C. & Li, Y. (2023) Simultaneous selection and inference for varying coefficients with zero regions: a soft-thresholding approach. Biometrics, 79, 3388–3401. https://doi.org/10.1111/biom.13900

Main script:

Follow "STV_example.R" to implement STV method.

Step 1. Load packages and functions. Paths need to be modified.

Step 2. Simulation. An example for setting is provided; here, $\beta_1$ is designed to have two turning points.

Step 3. Estimation. Examples for estumation using STV method, finding turning points, and bootstrapping are given. Note that the bootstrapping step may be time-consuming.

Step 4. Evaluation. We provide two datasets as the required inputs and then an example about bootstrap-based confidence intervals is shown here.

Additional files:

"STV_updated.R" contains functions in need to simulate data, estimate parameters, and evaluate results.

"STV_linear_cpp.cpp" contains functions in need to be used with "STV_updated.R".

"STV_example.Rmd" is a R Markdown version of "STV_example.R".

"STV_example.html" is the HTML document created by "STV_example.Rmd".

"wd_btsp_example.RData" and "wd_ori_example.RData" contain the example dataset as the required inputs for bootstrap-based confidence intervals