Kernelized Discriminant Analysis for Multivariate Categorical Response Regression

This repository provides the simulation code for the paper titled Kernelized Discriminant Analysis for Multivariate Categorical Response Regression.

Running the Simulation

To execute the simulation:

1. Open the Sim.sh file.

2. Replace all instances of XX in the Sim.sh file with the desired model code: A4, A6, B4, or B6.

For instance, to run the simulation for Model A-4:

#!/bin/bash
#SBATCH --job-name=KernelDA
#SBATCH -o Results-A4/Rep_%a.Rout
#SBATCH --array=1-1200
#SBATCH --mail-user=xxx@xyz
#SBATCH --mail-type=END
#SBATCH --account=abc
#SBATCH --qos=abc
#SBATCH --mem=2gb
#SBATCH -t 96:00:00

ml R/4.2
R CMD BATCH --vanilla Main-A4.R Results-A4/Rep_${SLURM_ARRAY_TASK_ID}.Rout

3. Create a directory to store the results.

mkdir Results-A4

4. Execute the modified Sim.sh file.

This process will launch 1200 jobs, corresponding to 100 replicates for each combination of:

• $p$ values: 50, 100, 150
• $\nu$ values: 0.8, 1.0, 1.2, 1.4

For every replicate, the script will execute Main-A4.R to generate data based on the specified data-generating model, fit various models, and assess their performance. All the results are saved in RDS files under the Results-A4 directory.

All necessary functions can be found in the Functions directory.