mse | R Documentation |
A generic function to compute the mean squared error of the predicted values under the estimated model. See also rfh for examples.
mse(object, ...)
## S3 method for class 'fitrfh'
mse(object, type = "pseudo", predType = "reblupbc", B = 100, ...)
object |
(see methods) an object containing the estimation result, e.g. rfh |
... |
arguments passed to methods |
type |
(character) the type of the MSE. Available are 'pseudo' and 'boot' |
predType |
(character) the type of prediction: |
B |
(numeric) number of bootstrap repetitions |
Type pseudo is an approximation of the MSE based on a pseudo linearisation approach by Chambers, et. al. (2011). The specifics can be found in Warnholz (2016). Type boot implements a parameteric bootstrap for these methods.
Chambers, R., H. Chandra and N. Tzavidis (2011). "On bias-robust mean squared error estimation for pseudo-linear small area estimators". In: Survey Methodology 37 (2), pp. 153–170.
Warnholz, S. (2016): "Small Area Estimaiton Using Robust Extension to Area Level Models". Not published (yet).
data("grapes", package = "sae")
data("grapesprox", package = "sae")
fitRFH <- rfh(
grapehect ~ area + workdays - 1,
data = grapes,
samplingVar = "var"
)
mseRFH <- mse(fitRFH)
plot(mseRFH)
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