sprbeta | R Documentation |
Simulate a spatial beta random variable with a specific mean and covariance structure.
sprbeta(
spcov_params,
dispersion = 1,
mean = 0,
samples = 1,
data,
randcov_params,
partition_factor,
...
)
spcov_params |
An |
dispersion |
The dispersion value. |
mean |
A numeric vector representing the mean. |
samples |
The number of independent samples to generate. The default
is |
data |
A data frame or |
randcov_params |
A |
partition_factor |
A formula indicating the partition factor. |
... |
Additional arguments passed to |
The values of spcov_params
, mean
, and randcov_params
are assumed to be on the link scale. They are used to simulate a latent normal (Gaussian)
response variable using sprnorm()
. This latent variable is the
conditional mean used with dispersion
to simulate a beta random variable.
If samples
is 1, a vector of random variables for each row of data
is returned. If samples
is greater than one, a matrix of random variables
is returned, where the rows correspond to each row of data
and the columns
correspond to independent samples.
spcov_params_val <- spcov_params("exponential", de = 0.2, ie = 0.1, range = 1)
sprbeta(spcov_params_val, data = caribou, xcoord = x, ycoord = y)
sprbeta(spcov_params_val, samples = 5, data = caribou, xcoord = x, ycoord = y)
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