rsglmm: Simulation from a spatial model

In geoBayes: Analysis of Geostatistical Data using Bayes and Empirical Bayes Methods

Simulation from a spatial model

Description

Simulate from a variety of spatial models.

Usage

rsglmm(
  n,
  formula,
  family = "gaussian",
  data,
  weights,
  subset,
  offset,
  atsample,
  beta,
  linkp,
  phi,
  omg,
  kappa,
  ssq,
  corrfcn = "matern",
  longlat = FALSE,
  dispersion = 1,
  returnGRF = FALSE,
  warndisp = TRUE
)

rstrga(
  n,
  formula,
  data,
  weights,
  subset,
  offset,
  atsample,
  beta,
  linkp,
  phi,
  omg,
  kappa,
  ssq,
  corrfcn = "matern",
  longlat = FALSE,
  dispersion = 1,
  returnGRF = FALSE
)

rsgrf(
  n,
  formula,
  data,
  subset,
  offset,
  atsample,
  beta,
  phi,
  omg,
  kappa,
  ssq,
  corrfcn = "matern",
  longlat = FALSE
)

Arguments

n	The number of instances to simulate
formula	A representation of the model in the form response ~ terms. The LHS can be omitted. If the LHS exists, it can be of the form y, y|z, or sums of terms at either side of the | to specify the names of the variables to include in the data frame.
family	The distribution of the data to simulate from.
data	An optional data frame containing the variables in the model.
weights	An optional vector of weights. Number of replicated samples for Gaussian and gamma, number of trials for binomial, time length for Poisson.
subset	An optional set of indices. Simulations will be provided for those locations only.
offset	See lm.
atsample	A formula of the form ~ Xcoord + Ycoord specifying the sampled locations.
beta	A vector of the regressor coefficents to use.
linkp	The link function parameter.
phi	The spatial range parameter.
omg	The relative nugget parameter.
kappa	The spatial smoothness parameter.
ssq	The partial sill parameter.
corrfcn	The correlation function to use.
longlat	How to compute the distance between locations. If FALSE, Euclidean distance, if TRUE Great Circle distance. See spDists.
dispersion	The fixed dispersion parameter. When this is not 1 and the sample is from a binomial or a Poisson distribution, no such distribution exists so an approximate sample is returned. Use with caution.
returnGRF	Whether to return the simulate Gaussian random field as well.
warndisp	Whether to warn when sampling from a quasi distribution. This is the case for binomial and Poisson when the dispersion is not one.

Details

The spatial Gaussian random field is simulated using the Cholesky decomposition of the covariance matrix.

The sample from a quasi distribution uses a hack which matches the mean and the variance of the distribution. See the source code for details.

Value

A data frame containing the predictors, sampling locations, optional weights, and samples.

Examples

## Not run: 
n <- 100
beta <- c(-2, 1)
phi <- .2
omg <- .3
linkp <- 0
ssq <- 1
l <- rep(10, n)
corrf <- "matern"
kappa <- .5
family <- "poisson"
Xcoord <- runif(n)
Ycoord <- runif(n)
f <- Xcoord + Ycoord
formula <- y|z ~ f
mydata <- rsglmm(1, formula, family, weights = l,
                 atsample = ~ Xcoord + Ycoord, beta = beta, linkp = linkp,
                 phi = phi, omg = omg, kappa = kappa, ssq = ssq,
                 corrfcn = corrf, returnGRF = TRUE)

## End(Not run)

geoBayes documentation built on Aug. 21, 2023, 9:08 a.m.