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Forum: Version 0.995 of the "frontier" package is ready

Posted by: Arne Henningsen
Date: 2009-09-21 08:20
Summary:Version 0.995 of the "frontier" package is ready
Project:frontier: Stochastic Frontier Analysis

Version 0.995 of the frontier package is ready for publication now. Binary and source packages will be available on R-Forge and CRAN soon.

This version has several improvements compared to previous versions.

Most notably, the new function "sfa" provides a user-interface for Stochastic Frontier Analysis (SFA) that is much more similar to other regression tools in R (e.g. "lm") than the old function "frontier". However, the latter function is kept for compatibility with older versions of this package; it is simply a wrapper function to "sfa" now,

Moreover, there are following significant changes in the new version:

* functions "sfa" (and hence also "frontier", "frontierQuad" etc.) no longer calculate and return efficiency estimates

* function "sfa" no longer has argument "logDepVar", because this information is irrelevant for the estimation

* method "efficiencies" for objects of class "frontier" calculates efficiency estimates now (instead of just extracting them)

* method "efficiencies" for objects of class "frontier" has the argument "logDepVar" now, which indicates whether the dependent variable is logged (this information is required to calculate the efficiency estimates)

* method "summary" for objects of class "frontier" calculates and returns the efficiency estimates now (the calculation is done by the "efficiencies" method, see above)

* method "summary" for objects of class "frontier" has the argument "logDepVar" now, which indicates whether the dependent variable is logged (this information is required to calculate the efficiency estimates)

* added "residuals" method for objects of class "frontier" to obtain the residuals

* fixed bug in the Fortran subroutine "der1" that calculates the derivatives of the likelihood function of the "Error Components Frontier" (ECF): in case of unbalanced panel data, uninitialized values (for unobserved observations) were used in the calculation so that the derivatives were wrong

* fixed bug in the Fortran code: in case of unbalanced panel data, the efficiency estimates of the missing observations were set to the previously calculated efficiency estimate (mostly the efficiency estimate of the previous firm in the same year)

* added further tests in /tests/frontierTest.R

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