ordermscore.boot {frontiles}

Calculates order-m efficiency score with bootstrap algorithm

Description

Calculates order-m efficiency score (output, input and hyperbolic direction) for a set of assessment points (xeval, yeval) depending on sample points (xobs, yobs), using the initial algorithm of Cazals et al. (2002).

Usage

ordermscore.boot(xobs, yobs, xeval=xobs, yeval=yobs, m=30, B=200, m.move=FALSE)

Arguments

xobs

a matrix of size n_1 \times p, input of sample points

yobs

a matrix of size n_1 \times q, output of sample points

xeval

a matrix of size n_2 \times p, input of assessment points

yeval

a matrix of size n_2 \times q, output of assessment points

m

an integer, the number of selected firms

B

an integer, the number of replication

m.move

a boolean, to choose different values of m

Details

This function computes the algorithm initially proposed by Cazals et al. (2002). If m.move=TRUE, different values of m are given as suggested by Daouia et al (2009).

Value

a data.frame object with the average mean order-m efficiency score and standard deviation associated:

output

output direction

output

output direction

input

input direction

input

input direction

hyper

hyperbolic direction

hyper

hyperbolic direction

Author(s)

Abdelaati Daouia and Thibault Laurent

References

Cazals et al. (2002), Nonparametric frontier estimation: a robust approach, Journal of Econometrics.

Daouia et al. (2009), Regularization of Nonparametric Frontier Estimators, TSE working paper.

See Also

ordermscore,alphascore

Examples

# 1st example
data(spain)
score.orderm.b <- ordermscore.boot(xobs = as.matrix(spain[, c(2, 3, 4)]),
                    yobs = as.matrix(spain[, 1]))

system.time(
  ordermscore.boot(xobs = as.matrix(spain[, c(2, 3, 4)]), 
                 yobs = as.matrix(spain[, 1]))
)
system.time(
  ordermscore(xobs = as.matrix(spain[, c(2, 3, 4)]),
              yobs = as.matrix(spain[, 1]))
)

# 2nd example

data(burposte)
ind.samp <- sample(nrow(burposte), 500)
xobs <- as.matrix(burposte[ind.samp[1:100], 2])
yobs <- as.matrix(burposte[ind.samp[1:100], 3])
xeval <- as.matrix(burposte[ind.samp[101:500], 2])
yeval <- as.matrix(burposte[ind.samp[101:500], 3])
score.orderm.2.b <- ordermscore.boot(xobs, yobs, xeval, yeval)