estimateParameters.psgp {psgp} | R Documentation |
This overloads the estimateParameters
routine
from the intamap package for interpolation using the PSGP method.
estimateParameters(object, ...)
object |
a list object of Intamap type. Most arguments necessary for interpolation are passed through this object. See intamap-package for further description of the necessary content of this variable. |
... |
other parameters for the generic method, not used for this method |
See psgp-package
and learnParameters
for
further details.
Remi Barillec, Ben Ingram
learnParameters
,
estimateParameters
,
makePrediction
,
createIntamapObject
# load our favourite dataset data(meuse) coordinates(meuse) = ~x+y meuse$value = log(meuse$zinc) data(meuse.grid) gridded(meuse.grid) = ~x+y proj4string(meuse) = CRS("+init=epsg:28992") proj4string(meuse.grid) = CRS("+init=epsg:28992") # the following two steps are only needed if one wishes to # include observation errors # indicate which likelihood model should be used for each observation # in this case we use a different model for each observation nobs = length(meuse$value) # Number of observations meuse$oeid <- seq(1:nobs) # the variances for the error models are random in this example # in real examples they will come from actual measurements # characteristics meuse$oevar <- abs( rnorm( max(meuse$oeid) ) ) # set up intamap object: obj = createIntamapObject( observations = meuse, predictionLocations = meuse.grid, targetCRS = "+init=epsg:3035", class = "psgp" # Use PSGP for parameter estimation/interpolation ) # do interpolation step: obj = conformProjections(obj) obj = estimateParameters(obj)