A Pollution Sensor Relation Conditional on Weather and Clock

Authors

  • Michael Franklin Author
  • Stephen Reynolds Author
  • Caleb Collins Author

Abstract

The question concerns cO sensor association conditional on weather and clock. The secondary ordinary least squares analysis contains 7,344 observations and uses cluster covariance. The coefficient on PT08_S1_CO is 0.0017, with a 95 percent interval from 0.0016 to 0.0017. A sensor-reference association can inform calibration-related modeling without establishing a stable ordering outside the observed environment. Model combination and regression subsets should be checked where local comparisons reverse. The complete-case sample is part of the estimand; no result for its sensor relation automatically describes hours excluded by missing measurements. The estimates describe the released collection and its conditioning set. No new data collection, simulator experiment, or deployment-policy evaluation is claimed.

References

F. Gao, Z. Shi, S. Gao, and H. Xiao, “Efficient Simulation Budget Allocation for Subset Selection Using Regression Metamodels,” Automatica, vol. 106, pp. 192–200, 2019.

S. Zhang, J. Xu, E. Huang, C.-H. Chen, and S. Gao, “Improving Ordinal Transformation through Optimal Combination of Multi-Model Predictions,” Proceedings of the 2016 IEEE International Conference on Industrial Technology, pp. 1545–1549, 2016.

Saverio Vito. Air Quality. UCI Machine Learning Repository, 2008. Dataset. https://doi.org/10.24432/C59K5F.

White, Halbert. “A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity.” Econometrica, vol. 48, no. 4, 1980, pp. 817–838. https://doi.org/10.2307/1912934.

Cameron, A. Colin, and Douglas L. Miller. “A Practitioner’s Guide to Cluster-Robust Inference.” Journal of Human Resources, vol. 50, no. 2, 2015, pp. 317–372. https://doi.org/10.3368/jhr.50.2.317.

Rasmussen, Carl Edward, and Christopher K. I. Williams. Gaussian Processes for Machine Learning. MIT Press, 2006. https://gaussianprocess.org/gpml/.

Ankenman, Bruce, Barry L. Nelson, and Jeremy Staum. “Stochastic Kriging for Simulation Metamodeling.” Operations Research, vol. 58, no. 2, 2010, pp. 371–382. https://doi.org/10.1287/opre.1090.0754.

Kim, Seong-Hee, and Barry L. Nelson. “A Fully Sequential Procedure for Indifference-Zone Selection in Simulation.” ACM Transactions on Modeling and Computer Simulation, vol. 11, no. 3, 2001, pp. 251–273. https://doi.org/10.1145/502109.502111.

Frazier, Peter I., Warren B. Powell, and Savas Dayanik. “A Knowledge-Gradient Policy for Sequential Information Collection.” SIAM Journal on Control and Optimization, vol. 47, no. 5, 2008, pp. 2410–2439. https://doi.org/10.1137/070693424.

Bertsimas, Dimitris, and Melvyn Sim. “The Price of Robustness.” Operations Research, vol. 52, no. 1, 2004, pp. 35–53. https://doi.org/10.1287/opre.1030.0065.

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Published

2026-04-18

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Articles