EAT_WAM {eat}

Weighted Additive Model for an Efficiency Analysis Trees model

Description

Weighted Additive Model for an Efficiency Analysis Trees model.

Usage

EAT_WAM(j, scores, x_k, y_k, atreeTk, ytreeTk, nX, nY, N_leaves, weights)

Arguments

j

Number of DMUs.

scores

matrix. Empty matrix for scores.

x_k

data.frame. Set of input variables.

y_k

data.frame Set of output variables.

atreeTk

matrix Set of "a" Pareto-coordinates.

ytreeTk

matrix Set of predictions.

nX

Number of inputs.

nY

Number of outputs.

N_leaves

Number of leaf nodes.

weights

Character. "MIP" for Measure of Inefficiency Proportion or "RAM" for Range Adjusted Measure of Inefficiency.

Value

A numerical vector with efficiency scores.