spatial.pred.poisson.MCML: Spatial predictions for the Poisson model with log link...
In PrevMap: Geostatistical Modelling of Spatially Referenced Prevalence Data

Description Usage Arguments Value Author(s)

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.

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
)

`object`	an object of class "PrevMap" obtained as result of a call to `poisson.log.MCML`.
`grid.pred`	a matrix of prediction locations.
`predictors`	a data frame of the values of the explanatory variables at each of the locations in `grid.pred`; each column correspond to a variable and each row to a location. Warning: the names of the columns in the data frame must match those in the data used to fit the model. Default is `predictors=NULL` for models with only an intercept.
`control.mcmc`	output from `control.mcmc.MCML`.
`type`	a character indicating the type of spatial predictions: `type="marginal"` for marginal predictions or `type="joint"` for joint predictions. Default is `type="marginal"`. In the case of a low-rank approximation only joint predictions are available.
`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 `scale.predictions=c("log","exponential")`.
`quantiles`	a vector of quantiles used to summarise the spatial predictions.
`standard.errors`	logical; if `standard.errors=TRUE`, then standard errors for each `scale.predictions` are returned. Default is `standard.errors=FALSE`.
`thresholds`	a vector of exceedance thresholds; default is `thresholds=NULL`.
`scale.thresholds`	a character value indicating the scale on which exceedance thresholds are provided; `"log"` or `"exponential"`. Default is `scale.thresholds=NULL`.
`plot.correlogram`	logical; if `plot.correlogram=TRUE` the autocorrelation plot of the conditional simulations is displayed.
`messages`	logical; if `messages=TRUE` then status messages are printed on the screen (or output device) while the function is running. Default is `messages=TRUE`.

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.

Emanuele Giorgi e.giorgi@lancaster.ac.uk

Peter J. Diggle p.diggle@lancaster.ac.uk

PrevMap documentation built on Oct. 7, 2021, 5:07 p.m.