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Last data update: 2014.03.03

R: Calculates order-m efficiency score with bootstrap algorithm

ordermscore.boot

R Documentation

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 n1 x p, input of sample points
`yobs`	a matrix of size n1 x q, output of sample points
`xeval`	a matrix of size n2 x p, input of assessment points
`yeval`	a matrix of size n2 x 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.

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)