Wavelet-based Bayesian nonlinear regression for the air pollution effects on clinic visits in small areas of Taiwan
Communications in Statistics: Simulation and Computation
We revisit the complete clinic visit records and environmental monitoring data at 50 townships and city districts of Taiwan. Extending the earlier analyses, here we consider a Bayesian analysis using Daubechies wavelet. Appropriate model selection is also considered using Bayesian model averaging. Temperature, dew point, and NO2 and CO of the current day and the previous day are identified as the pollutants in different areas of the island following some spatial pattern.
Angers, Jean François; Biswas, Atanu; and Hwang, Jing Shiang, "Wavelet-based Bayesian nonlinear regression for the air pollution effects on clinic visits in small areas of Taiwan" (2017). Journal Articles. 2456.