Produces a pca plot with spatial variation in localisation probabilities
spatial2D(
object,
dims = c(1, 2),
cov.function = fields::wendland.cov,
theta = 1,
derivative = 2,
k = 1,
breaks = c(0.99, 0.95, 0.9, 0.85, 0.8, 0.75, 0.7),
aspect = 0.5
)
A valid object of class MSnset
with mcmc prediction
results from tagmMCMCpredict
The PCA dimension in which to project he data, default is
c(1,2)
The covariance function used default is
wendland.cov. See fields
package.
A hyperparameter to the covariance function. See fields
package. Default is 1.
The number of derivative of the wendland kernel. See
fields
package. Default is 2.
A hyperparamter to the covariance function. See fields
package. Default is 1.
Probability values at which to draw the contour bands. Default
is c(0.99, 0.95, 0.9, 0.85, 0.8, 0.75, 0.7)
A argument to change the plotting aspect of the PCA
Used for side effect of producing plot. Invisibily returns an ggplot object that can be further manipulated
if (FALSE) {
library("pRolocdata")
data("tan2009r1")
tanres <- tagmMcmcTrain(object = tan2009r1)
tanres <- tagmMcmcProcess(tanres)
tan2009r1 <- tagmMcmcPredict(object = tan2009r1, params = tanres, probJoint = TRUE)
spatial2D(object = tan2009r1)
}