gainML: Preparation and Implementation

Hoon Hwangbo


This documents illustrates how to prepare data, how to implement the package, and what the resulting objects are.

Data preparation

For the analysis, this package requires to use at least three turbine datasets (dataframes); one for each of reference turbine, baseline control turbine, and neutral control turbine.


To use the package, a user first needs to load the package (attach the package to the current R environment).


Point estimation of gain

Once the package is loaded, a user can (i) simply run a single function analyze.gain or (ii) choose to run multiple functions in sequence (analyze.gain basically runs these functions in sequence).

For the details about the functions, please refer to the package manual (in a pdf format).

Interval estimation of gain (by using bootstrap)

Once the package is loaded, a user needs to run a series of functions as illustrated below.


Resulting Objects

The analysis outcome can be obtained from the quantify.gain function (the return from analyze.gain and bootstrap.gain will also include this outcome). The outcome includes:

Please refer to the package manual for more details.