Spatial statistical models that use flow and stream distance

By Jay M. Ver Hoef, Erin E. Peterson, David M. Theobald. Environmental and Ecological Statistics, 2006

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Kernel Density Estimation on a Linear Network (2017, background): “…Okunuki & Okabe, 2003; Comber et al., 2008); insect nests (Voss et al., 2007; Ang et al., 2012); neuroanatomical features (Yadav et al., 2012; Jammalamadaka et al., 2013; Baddeley et al., 2014); or sample points along a stream (Ver Hoef et al., 2006; Ver Hoef & Peterson, 2010; Som et al., 2014).”
Second-order non-stationary modeling approaches for univariate geostatistical data (2017, methodology): “Nychka and Saltzman (1998) and Holland et al. (1999) extend the random function model defined in Eq. (7) by representing a non-stationary random function as a sum of an isotropic stationary random function and a linear combination of basis functions. The latter sum representing the departure from th”
The role of dispersal in river network metacommunities: Patterns, processes, and pathways (2018, methodology): “1243 Peterson, E. E., Ver Hoef, J. M., Isaak, D. J., Falke, J. a, Fortin, M.-J., Jordan, C. E., … Wenger, 1244 S. J. (2013).”
Process (2020, methodology): “Thus, the random variable of the other observable location can be developed as the integration of moving average function of this white noise process along the road network [33].”
Some topics in convolution-based spatial modeling (2007, neutral): “Ver Hoef et al. (2006) and Cressie t al.”