AVEMSE: Calculate average mean squared error (aMSE) with...

In TSE: Total Survey Error

Description

Calculates average mean squared error (aMSE) with bias-variance decomposition for one or more surveys

Usage

AVEMSE(Actuals1 = data.frame(), Observed1 = data.frame(), ...)

Arguments

Actuals1	= data from a "gold standard" survey; objects are variable columns from "gold standard" survey that corruspond to variable columns Observed1
Observed1	= data from survey 1; objects are variable columns from survey 1 that corruspond to variable columns from Actuals1
...	= "gold standard" data/survey # data for additional surveys

Details

aMSE for survey # => mean value of the MSEs for specified variables in survey # => mean value of MSEs for objects in Observed#=data.frame()

Value

Average mean squared error (aMSE) with bias-variance decomposition

Note

Make sure to properly order inputs, per the example: Actuals1=data.frame() objects and corrusponding Observed1=data.frame() objects must be given in the same order as each other; and ... must be given in numbered pairs of Actuals#, Observed#, and those pairs given in sequence of their #s.

Examples

AVEMSE(Actuals1=data.frame(TESTNUMB$AQ1, TESTNUMB$AQ2),
Observed1=data.frame(TESTNUMB$O1Q1, TESTNUMB$O1Q2),
Actuals2=data.frame(TESTNUMB$AQ1, TESTNUMB$AQ2),
Observed2=data.frame(TESTNUMB$O2Q1, TESTNUMB$O2Q2),
Actuals3=data.frame(TESTNUMB$AQ1, TESTNUMB$AQ2),
Observed3=data.frame(TESTNUMB$O3Q1, TESTNUMB$O3Q2))

Example output

                 aMSE         aBias^2     aVar   
   survey 1  =>   963.50  =>    2.740  +  960.760
   survey 2  =>   965.60  =>   25.490  +  940.110
   survey 3  =>  1029.65  =>  307.765  +  721.885

TSE documentation built on June 20, 2019, 5:03 p.m.