Description Usage Arguments Details Value Note Examples
Calculates average mean squared error (aMSE) with bias-variance decomposition under multiple, different weighting schemes
1 2 | AVEMSEw(Actual = data.frame(), Survey = data.frame(),
Weights = data.frame())
|
Actual |
data from a "gold standard" survey; objects are variable columns from "gold standard" survey that corruspond to variable columns Survey |
Survey |
data from a survey; objects are variable columns from a survey that corruspond to variable columns from Actual |
Weights |
weights to be applied to Survey data; objects are weights columns |
aMSE for weighting scheme # => mean value of the MSEs for specified variables under weighting scheme # => mean value of MSEs for objects in Survey=data.frame() * objects in Weights=data.frame()
Average mean squared error (aMSE) with bias-variance decomposition under multiple, different weighting schemes
Make sure to properly order inputs, per the example: Actual=data.frame() objects and corrusponding Survey=data.frame() objects must be given in the same order as each other; and Weights=data.frame() objects must be given in sequence of weighting scheme #.
1 2 3 | AVEMSEw(Actual=data.frame(TESTWGT$A1, TESTWGT$A2),
Survey=data.frame(TESTWGT$Q1, TESTWGT$Q2),
Weights=data.frame(TESTWGT$W1, TESTWGT$W2))
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