ordermscore {frontiles}

Calculates order-m efficiency score with asymptotic formula

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 formulas of Daouia and Gijbels (2011).

Usage

ordermscore(xobs, yobs, xeval=xobs, yeval=yobs, m=30)

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

Details

A score between 0 and 1 means that DMU is inefficient. If DMU greater than 1, DMU is super-efficient. The asymptotic formula of the order-m score are given in Daouia and Gijbels (2011).

Value

a data.frame object with the order-m efficiency score in:

output

output direction

input

input direction

hyper

hyperbolic direction

Author(s)

Abdelaati Daouia and Thibault Laurent

References

Daouia and Gijbels (2011), Robustness and inference in nonparametric partial-frontier modeling, Journal of Econometrics.

See Also

alphascore, ordermfrontier.2d

Examples

# 1st example
data(spain)
score.orderm<-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 <- ordermscore(xobs, yobs, xeval, yeval)