AVEMSLEw function

Average mean squared logarithmic error (aMSLE)

Average mean squared logarithmic error (aMSLE)

Calculates average mean squared logarithmic error (aMSLE) under multiple, different weighting schemes

AVEMSLEw(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

Returns

Average mean squared logarithmic error (aMSLE) under multiple, different weighting schemes

Details

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

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

AVEMSLEw(Actual=data.frame(TESTWGT$A1, TESTWGT$A2), Survey=data.frame(TESTWGT$Q1, TESTWGT$Q2), Weights=data.frame(TESTWGT$W1, TESTWGT$W2))
  • Maintainer: Joshua Miller
  • License: GPL (>= 2)
  • Last published: 2019-07-02

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