2021.0329

This archive is distributed in association with the INFORMS Journal on Computing under the MIT License.

The scripts in this repository are a snapshot of the scripts that were used in the research reported on in the paper Convergence Analysis of Stochastic Kriging-Assisted Simulation with Random Covariates by C. Li, S. Gao and J. Du.

Cite

To cite this software, please cite the paper -- Convergence Analysis of Stochastic Kriging-Assisted Simulation with Random Covariates -- using its DOI and the software itself using the following DOI.

Below is the BibTex for citing this version of the code.

@article{li2022,
  author =        {C. Li, S. Gao and J. Du},
  publisher =     {INFORMS Journal on Computing},
  title =         {Convergence Analysis of Stochastic Kriging-Assisted Simulation with Random Covariates},
  year =          {2022},
  doi =           {10.5281/zenodo.7344997},
  url =           {Available for download at https://github.com/INFORMSJoC/2021.0329},
}  

Description

The goal of this repository is to illustrate the the convergence behaviors of stochastic kriging-assisted simulation with random covariates.

Requirements

For this project, we use Matlab. The user should respect the license of the used sotfware.

Repository Structure

Scripts

• "scripts/d1" folder:  testing the rates of maximal IMSE and IPFS under the random sampling and comparing the random design with the Adaptive MSE procedure in the one-dimensional benchmark function examples,
• "scripts/d2" folder:  testing the rates of maximal IMSE and IPFS under the random sampling and comparing the random design with the Adaptive MSE procedure in the two-dimensional benchmark function examples,
• "scripts/d3" folder:  testing the rates of maximal IMSE and IPFS under the random sampling and comparing the random design with the Adaptive MSE procedure in the three-dimensional benchmark function examples,
• "scripts/d10" folder: testing the rates of maximal IMSE and IPFS under the random sampling and comparing the random design with the Adaptive MSE procedure in the ten-dimensional benchmark function examples.
• "scripts/queue" folder: testing the rates of maximal IMSE and IPFS under the random sampling and showing how the theory can help decide the sample size to achieve a target precision in the M/M/1 queue example.

Results

The online supplement of this paper is also in this subdirectory. The following tells the corresponding script for each result of the numerical experiment.

Figures in manuscript:

• “Figure 1” of the manuscript (i.e., results/Figure1(1).png and results/Figure1(2).png of this repository): obtained by running "scripts/d1/AdapMSE.m" (main part: Lines 23-35 and 163-264) in the "scripts/d1" folder

• “Figure 2” of the manuscript (i.e., results/Figure2(1).png and results/Figure2(2).png of this repository): obtained by running "scripts/d1/AdapMSE2.m" (main part: Lines 23-35 and 164-268) in the "scripts/d1" folder

• “Figure 3” of the manuscript (i.e., results/Figure3(1).png and results/Figure3(2).png of this repository): obtained by running "scripts/d3/Adap13D.m" (main part: Lines 23-35 and 73-174) in the "scripts/d3" folder

• “Figure 4” of the manuscript (i.e., results/Figure4(1).png and results/Figure4(2).png of this repository): obtained by running "scripts/d10/Adap10D.m" (main part: Lines 22-35 and 164-257) in the "scripts/d10" folder

• “Figures 5 and 6” of the manuscript (i.e., results/Figure5.png and results/Figure6.png of this repository): obtained by running "scripts/queue/manuscript/AdapQ.m" in the "scripts/queue/manuscript" folder

Figures in online supplement:

• “Figure 3” of the online supplement (i.e., results/OS52Case1(1).png and results/OS52Case1(2).png of this repository): obtained by running "scripts/d1/AdapMSE.m" (main part: Lines 66-95 and 265-328) in the "scripts/d1" folder

• “Figure 4” of the online supplement (i.e., results/OS52Case2(1).png and results/OS52Case2(2).png of this repository): obtained by running "scripts/d1/AdapMSE.m" (main part: Lines 36-65 and 98-162) in the "scripts/d1" folder

• “Figure 5” of the online supplement (i.e., results/OS52Case3(1).png and results/OS52Case3(2).png of this repository): obtained by running "scripts/d2/Adap12D.m" (main part: Lines 38-67 and 73-140) in the "scripts/d2" folder

• “Figure 6” of the online supplement (i.e., results/OS52Case4(1).png and results/OS52Case4(2).png of this repository): obtained by running "scripts/d3/Adap13D.m" (main part: Lines 36-66 and 175-241) in the "scripts/d3" folder

• “Figure 7” of the online supplement (i.e., results/OS52Case5(1).png and results/OS52Case5(2).png of this repository): obtained by running "scripts/d1/AdapMSE2.m" (main part: Lines 66-89 and 269-338) in the "scripts/d1" folder

• “Figure 8” of the online supplement (i.e., results/OS52Case6(1).png and results/OS52Case6(2).png of this repository): obtained by running "scripts/d1/AdapMSE2.m" (main part: Lines 36-65 and 93-160) in the "scripts/d1" folder

• “Figure 9” of the online supplement (i.e., results/OS52Case7(1).png and results/OS52Case7(2).png of this repository): obtained by running "scripts/d10/Adap10D.m" (main part: Lines 66-90 and 261-329) in the "scripts/d10" folder

• “Figure 10” of the online supplement (i.e., results/OS52Case8(1).png and results/OS52Case8(2).png of this repository): obtained by running "scripts/d10/Adap10D.m" (main part: Lines 36-65 and 93-161) in the "scripts/d10" folder

Table in online supplement:

• Table of Online Supplement's Section 5.3: obtained by running "scripts/queue/online supplement/Queue_pred.m" in the "scripts/queue/online supplement" folder