spatial2D {pRoloc} | R Documentation

## Uncertainty plot in localisation probabilities

### Description

Produces a pca plot with spatial variation in localisation probabilities

### Usage

    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)

### Arguments

`object` | A valid object of class `MSnset` with mcmc prediction results from `tagmMCMCpredict`
`dims` | The PCA dimension in which to project he data, default is `c(1,2)`
`cov.function` | The covariance function used default is wendland.cov. See `fields` package.
`theta` | A hyperparameter to the covariance function. See `fields` package. Default is 1.
`derivative` | The number of derivative of the wendland kernel. See `fields` package. Default is 2.
`k` | A hyperparamter to the covariance function. See `fields` package. Default is 1.
`breaks` | 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)`
`aspect` | A argument to change the plotting aspect of the PCA

### Value

Used for side effect of producing plot. Invisibily returns an ggplot object that can be further manipulated

### Author(s)

Oliver M. Crook <omc25@cam.ac.uk>

### Examples

    ## Not run:
    library("pRolocdata")
    data("tan2009r1")

    tanres <- tagmMcmcTrain(object = tan2009r1)
    tanres <- tagmMcmcProcess(tanres)
    tan2009r1 <- tagmMcmcPredict(object = tan2009r1, params = tanres, probJoint = TRUE)
    spatial2D(object = tan2009r1)

    ## End(Not run)

[Package pRoloc version 1.30.0 Index]