spatial.pred.poisson.MCML {PrevMap} | R Documentation |
Spatial predictions for the Poisson model with log link function, using plug-in of MCML estimates
Description
This function performs spatial prediction, fixing the model parameters at the Monte Carlo maximum likelihood estimates of a geostatistical Poisson model with log link function.
Usage
spatial.pred.poisson.MCML(
object,
grid.pred,
predictors = NULL,
control.mcmc,
type = "marginal",
scale.predictions = c("log", "exponential"),
quantiles = c(0.025, 0.975),
standard.errors = FALSE,
thresholds = NULL,
scale.thresholds = NULL,
plot.correlogram = FALSE,
messages = TRUE
)
Arguments
object |
an object of class "PrevMap" obtained as result of a call to |
grid.pred |
a matrix of prediction locations. |
predictors |
a data frame of the values of the explanatory variables at each of the locations in |
control.mcmc |
output from |
type |
a character indicating the type of spatial predictions: |
scale.predictions |
a character vector of maximum length 2, indicating the required scale on which spatial prediction is carried out: "log" and "exponential". Default is |
quantiles |
a vector of quantiles used to summarise the spatial predictions. |
standard.errors |
logical; if |
thresholds |
a vector of exceedance thresholds; default is |
scale.thresholds |
a character value indicating the scale on which exceedance thresholds are provided; |
plot.correlogram |
logical; if |
messages |
logical; if |
Value
A "pred.PrevMap" object list with the following components: log
; exponential
; exceedance.prob
, corresponding to a matrix of the exceedance probabilities where each column corresponds to a specified value in thresholds
; samples
, corresponding to a matrix of the predictive samples at each prediction locations for the linear predictor of the Poisson model (if scale.predictions="log"
this component is NULL
); grid.pred
prediction locations.
Each of the three components log
and exponential
is also a list with the following components:
predictions
: a vector of the predictive mean for the associated quantity (log or exponential).
standard.errors
: a vector of prediction standard errors (if standard.errors=TRUE
).
quantiles
: a matrix of quantiles of the resulting predictions with each column corresponding to a quantile specified through the argument quantiles
.
Author(s)
Emanuele Giorgi e.giorgi@lancaster.ac.uk
Peter J. Diggle p.diggle@lancaster.ac.uk