This function calculates the Mean Square Error between the predicted value and the observations in a given node.

Functions are provided to determine production frontiers and technical
efficiency measures through non-parametric techniques based upon regression trees.
The package includes code for estimating radial input, output, directional and
additive measures, plotting graphical representations of the scores and the production
frontiers by means of trees, and determining rankings of importance of input variables
in the analysis. Additionally, an adaptation of Random Forest by a set of individual
Efficiency Analysis Trees for estimating technical efficiency is also included. More
details in: <doi:10.1016/j.eswa.2020.113783>.

Miriam Esteve

Efficiency Analysis Trees

Víctor España

Juan Aparicio

Xavier Barber

mse function

<dl><dt>data</dt>
<dd>Data to be used.</dd>
<dt>t</dt>
<dd>A given node.</dd>
<dt>y</dt>
<dd>Column output indexes in data.</dd></dl>

Arguments

Mean Squared Error — mse

<dl>

<dt>data</dt>
<dd>Data to be used.</dd>


<dt>t</dt>
<dd>A given node.</dd>


<dt>y</dt>
<dd>Column output indexes in data.</dd>

</dl>

mse: Mean Squared Error

Description

Usage

Value

Arguments