Simulate values from a GMRF using a tail-up exponential model on a stream network
Usage
simulate_sfnetwork(sfnetwork_mesh, theta, n = 1, what = c("samples", "Q"))Arguments
- sfnetwork_mesh
Output from
sfnetwork_mesh- 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