intamap (version 1.4-9)

methodParameters: generate string for generation of method parameters

Description

function that generates a parsable string of identified method parameters for an intamap interpolation object

Usage

# S3 method for default
methodParameters(object)
# S3 method for copula
methodParameters(object)
# S3 method for idw
methodParameters(object)

Arguments

object

a list object. Most arguments necessary for interpolation are passed through this object. See intamap-package for further description of the necessary content of this variable

Value

A string that, when parsed, will recreate the methodParameters

Details

The function creates a text-string that makes it possible to add the the method parameters (anisotropy and idw-parameter, variogram model or copula parameters) to the object in a later call to createIntamapObject or interpolate without having to re-estimate the parameters. This function is particularly useful when interpolate is called from a Web Processing Service, and the user wants to reuse the method parameters. The function is mainly assumed to be called from within interpolate.

The default method assumes a variogram model of gstat type, e.g. a variogram similar to what can be created with a call to vgm. Also psgp uses this variogram model.

References

Pebesma, E., Cornford, D., Dubois, G., Heuvelink, G.B.M., Hristopulos, D., Pilz, J., Stohlker, U., Morin, G., Skoien, J.O. INTAMAP: The design and implementation f an interoperable automated interpolation Web Service. Computers and Geosciences 37 (3), 2011.

Examples

Run this code
# NOT RUN {
data(meuse)
coordinates(meuse) = ~x+y
meuse$value = log(meuse$zinc)
# set up intamap object:
krigingObject = createIntamapObject(
		observations = meuse,
		formulaString = as.formula('value~1'),class = "automap")
# do estimation steps:
krigingObject = estimateParameters(krigingObject)
krigingObject = methodParameters(krigingObject)

# Create a new object
krigingObject2 = createIntamapObject(observations = meuse,
		formulaString = as.formula('value~1'),
    params = list(methodParameters = krigingObject$methodParameters))

krigingObject$variogramModel
krigingObject2$variogramModel

# }

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