conditional/unconditional spatio-temporal simulation based on turning bands
krigeSTSimTB(formula, data, newdata, modelList, nsim, progress = TRUE,
nLyrs = 500, tGrid = NULL, sGrid = NULL, ceExt = 2, nmax = Inf)a spatio-temporal data frame with nSim simulations
the formula of the kriging predictor
conditioning data
locations in space and time where the simulation is carried out
the spatio-temporal variogram (from vgmST) defining the spatio-temporal covariance structure of the simulated Gaussian random field
number of simulations
boolean; whether the progress should be shown in progress bar
number of layers used in the turning bands approach (default = 500)
optional explicit temporal griding that shall be used
optional explicit spatial griding that shall be used
expansion in the circulant embedding, defaults to 2
number of nearest neighbours that shall e used, defaults to 'Inf' meaning all available points are used
Benedikt Graeler
Turning bands
Lantuejoul, C. (2002) Geostatistical Simulation: Models and Algorithms. Springer.
Matheron, G. (1973). The intrinsic random functions and their applications. Adv. Appl. Probab., 5, 439-468.
Strokorb, K., Ballani, F., and Schlather, M. (2014) Tail correlation functions of max-stable processes: Construction principles, recovery and diversity of some mixing max-stable processes with identical TCF. Extremes, Submitted.
Turning layers
Schlather, M. (2011) Construction of covariance functions and unconditional simulation of random fields. In Porcu, E., Montero, J.M. and Schlather, M., Space-Time Processes and Challenges Related to Environmental Problems. New York: Springer.
krigeSimCE
# see demo('circEmbeddingMeuse')
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