ltsk library is a collection of programs for implementing local spatial and local spatiotemporal Kriging. Unlike global Kriging, ltsk subsets the sample around a given location and time where predicted is needed; estimates variogram using the subset of sample data. Product-sum model is implemented and automatically estimated using the data points within the local neighbourhood. A unique advantage of ltsk is that it addresses non-stationarity, which is difficult to handle in large spatiotemporal dataset.
Naresh Kumar (NKumar@med.miami.edu) Dong Liang (email@example.com) Jun chen (firstname.lastname@example.org) Jin Chen (email@example.com)
Haas, Timothy C. "Local prediction of a spatio-temporal process with an application to wet sulfate deposition." Journal of the American Statistical Association 90.432 (1995): 1189-1199.
Iaco, S. De & Myers, D. E. & Posa, D., 2001. "Space-time analysis using a general product-sum model," Statistics & Probability Letters, Elsevier, vol. 52(1), pages 21-28, March.
Kumar, N., et al. (2013). "Satellite-based PM concentrations and their application to COPD in Cleveland, OH." Journal of Exposure Science and Environmental Epidemiology 23(6): 637-646.
Liang, D. and N. Kumar (2013). "Time-space Kriging to address the spatiotemporal misalignment in the large datasets." Atmospheric Environment 72: 60-69.
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