simulate_sfnetwork {tinyVAST} | R Documentation |
Simulate GMRF for stream network
Description
Simulate values from a GMRF using a tail-down (flow-unconnected) exponential model on a stream network
Usage
simulate_sfnetwork(sfnetwork_mesh, theta, n = 1, what = c("samples", "Q"))
Arguments
sfnetwork_mesh |
Output from |
theta |
Decorrelation rate |
n |
number of simulated GMRFs |
what |
Whether to return the simulated GMRF or its precision matrix |
Value
a matrix of simulated values for a Gaussian Markov random field
arising from a stream-network spatial domain, with row for each spatial random
effect and n
columns, using the sparse precision matrix
defined in Charsley et al. (2023)
References
Charsley, A. R., Gruss, A., Thorson, J. T., Rudd, M. B., Crow, S. K., David, B., Williams, E. K., & Hoyle, S. D. (2023). Catchment-scale stream network spatio-temporal models, applied to the freshwater stages of a diadromous fish species, longfin eel (Anguilla dieffenbachii). Fisheries Research, 259, 106583. doi:10.1016/j.fishres.2022.106583