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Combining heterogeneous spatial datasets with process-based spatial fusion models: A unifying framework., and . Comput. Stat. Data Anal., (2021)Spatial model fitting for large datasets with applications to climate and microarray problems., and . Stat. Comput., 19 (2): 113-128 (2009)Challenges in Combining Projections from Multiple Climate Models, , , , and . J. Climate, 23 (10): 2739--2758 (Dec 28, 2010)Advancing Texture Metrics to Model Landscape Heterogeneity., , , , and . IGARSS, page 2735-2738. IEEE, (2020)rasterdiv - an Information Theory tailored R package for measuring ecosystem heterogeneity from space: to the origin and back, , , , , , , , , and 25 other author(s). Methods in Ecology and Evolution, (2021)Additive Bayesian Network Modelling with the R Package abn., , , , and . CoRR, (2019)Joint variable selection of both fixed and random effects for Gaussian process-based spatially varying coefficient models., , and . Int. J. Geogr. Inf. Sci., 36 (12): 2525-2548 (2022)Additive Bayesian Network Modeling with the R Package abn., , , , and . J. Stat. Softw., (2023)dotCall64: An R package providing an efficient interface to compiled C, C++, and Fortran code supporting long vectors., , and . SoftwareX, (2018)BiasBed - Rigorous Texture Bias Evaluation., , , , , and . CVPR, page 22221-22230. IEEE, (2023)