AVEMSEw {TSEwgt} | R Documentation |
Average mean squared error (aMSE) with bias-variance decomposition
Description
Calculates average mean squared error (aMSE) with bias-variance decomposition under multiple, different weighting schemes
Usage
AVEMSEw(Actual = data.frame(), Survey = data.frame(),
Weights = data.frame())
Arguments
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 |
Details
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()
Value
Average mean squared error (aMSE) with bias-variance decomposition under multiple, different weighting schemes
Note
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 #.
Examples
AVEMSEw(Actual=data.frame(TESTWGT$A1, TESTWGT$A2),
Survey=data.frame(TESTWGT$Q1, TESTWGT$Q2),
Weights=data.frame(TESTWGT$W1, TESTWGT$W2))