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  "Title": "Nonparametric Modeling and Monitoring of Spatio-Temporal Data",
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  "Date": "2023-9-29",
  "Description": "Spatio-temporal data have become increasingly popular in\nmany research fields. Such data often have complex structures\nthat are difficult to describe and estimate. This package\nprovides reliable tools for modeling complicated\nspatio-temporal data. It also includes tools of online process\nmonitoring to detect possible change-points in a\nspatio-temporal process over time. More specifically, the\npackage implements the spatio-temporal mean estimation\nprocedure described in Yang and Qiu (2018)\n<doi:10.1002/sim.7622>, the spatio-temporal covariance\nestimation procedure discussed in Yang and Qiu (2019)\n<doi:10.1002/sim.8315>, the three-step method for the joint\nestimation of spatio-temporal mean and covariance functions\nsuggested by Yang and Qiu (2022)\n<doi:10.1007/s10463-021-00787-2>, the spatio-temporal disease\nsurveillance method discussed in Qiu and Yang (2021)\n<doi:10.1002/sim.9150> that can accommodate the covariate\neffect, the spatial-LASSO-based process monitoring method\nproposed by Qiu and Yang (2023)\n<doi:10.1080/00224065.2022.2081104>, and the online\nspatio-temporal disease surveillance method described in Yang\nand Qiu (2020) <doi:10.1080/24725854.2019.1696496>.",
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        "SpTe2M"
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