stSimulate: Simulate responses from the spatio-temporal teleconnection...
In telefit: Estimation and Prediction for Remote Effects Spatial Process Models

This function simulates spatio-temporal data. The intention is that data Y and latent parameters alpha will be generated using provided covariates X and Z; spatial domains coords.s, coords.r, and coords.knots; and model parameters.

1	stSimulate(dat.train, dat.test, coords.knots, params, miles = T)

`dat.train`	stData object with training data to simulate new Y values for
`dat.test`	stData object with test data to simulate new Y values for
`coords.knots`	matrix with coordinates of knots for remote covariates (lon, lat)
`params`	A list containing model parameters for use in simulation beta vector with fixed effect coefficients cov.s list(smoothness=double, range=double, variance=double, nugget=double) cov.r list(smoothness=double, range=double, variance=double, nugget=double)
`miles`	TRUE to compute distances for evaluating covariance functions in miles. This is important since the interpretations of the cov.r and cov.s parameters depend on the units with which distance is measured.

set.seed(2018)
  
data("coprecip")
data("coprecip.fit")

coprecip.predict = stPredict(stFit = coprecip.fit, stData = coprecip, 
                             stDataNew = coprecip, burn = 90, 
                             returnFullAlphas = FALSE)