AVEMSLEw: Average mean squared logarithmic error (aMSLE)

In TSEwgt: Total Survey Error Under Multiple, Different Weighting Schemes

Description

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

Usage

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

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()

Value

Average mean squared logarithmic error (aMSLE) 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

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

TSEwgt documentation built on July 2, 2019, 5:03 p.m.