| AVERSE {TSE} | R Documentation |
Calculate average relative squared error (aRSE)
Description
Calculates average relative squared error (aRSE) for one or more surveys
Usage
AVERSE(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
aRSE for survey # => mean value of the RSEs for specified variables in survey # => mean value of RSEs for objects in Observed#=data.frame()
Value
Average relative squared error (aRSE)
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
AVERSE(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))