The dataset is concerned with the assessment of the efficiency of 37 European Air Controllers. The performance of each controller can be measured by its ``distance'' 
from the upper support boundary, or equivalently, the set of the most efficient controllers. This dataset is taken from Mouchart and Simar (2002). 
Here, the activity of the controllers is described by one input (an aggregate factor of different kind of labor) 
and one output (an aggregate factor of the activity produced, based on the number of controlled air movements, the number of controlled flight hours, etc.). 
See also Daouia, Florens and Simar (2008).

datasets

A variety of functions for the best known and most innovative approaches to nonparametric boundary estimation. The selected methods are concerned with empirical, smoothed, unrestricted as well as constrained fits under both separate and multiple shape constraints. They cover robust approaches to outliers  as well as data envelopment techniques based on piecewise polynomials, splines, local linear fitting, extreme values and kernel smoothing. The package also seamlessly allows for Monte Carlo comparisons among these different estimation methods.  Its use is illustrated via a number of empirical applications and simulated examples.

Thibault Laurent

npbr

Nonparametric Boundary Regression

air function

A data frame with 37 observations on the following 2 variables.<dl>
 <dt><code>xtab</code></dt>
<dd>an input.</dd> <dt><code>ytab</code></dt>
<dd>an output.</dd> 
</dl>

Format

European air controllers — air

A data frame with 37 observations on the following 2 variables.<dl>
 <dt><code>xtab</code></dt>
<dd>an input.</dd>

 <dt><code>ytab</code></dt>
<dd>an output.</dd>

 
</dl>

air: European air controllers

Description

Usage

Arguments

Format

References

Examples