R: Average relative squared error (aRSE)

AVERSEw

R Documentation

Average relative squared error (aRSE)

Description

Calculates average relative squared error (aRSE) under multiple, different weighting schemes

Usage

AVERSEw(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

aRSE for weighting scheme # => mean value of the aRSEs for specified variables under weighting scheme # => mean value of aRSEs for objects in Survey=data.frame() * objects in Weights=data.frame()

Value

Average relative squared error (aRSE) 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

AVERSEw(Actual=data.frame(TESTWGT$A1, TESTWGT$A2),
Survey=data.frame(TESTWGT$Q1, TESTWGT$Q2),
Weights=data.frame(TESTWGT$W1, TESTWGT$W2))