** FuzzyNumbers Package CHANGELOG ** *************************************************************************** 0.3-3 /2014-01-03/ * piecewiseLinearApproximation() now supports new method="SupportCorePreserving", see Coroianu L., Gagolewski M., Grzegorzewski P., Adabitabar Firozja M., Houlari T., Piecewise Linear Approximation of Fuzzy Numbers Preserving the Support and Core, 2014 (submitted for publication). * piecewiseLinearApproximation() now does not fail on exceptions thrown by integrate(); fallback=Newton-Cotes formula. * Removed `Suggests` dependency: testthat tests now available for developers via the FuzzyNumbers github repository. * Package manual has been corrected and extended. * Package vignette is now only available online at http://FuzzyNumbers.rexamine.com.
Abstract: The Choquet, Sugeno, and Shilkret integrals with respect to monotone measures, as well as their generalization – the universal integral, stand for a useful tool in decision support systems. In this paper we propose a general construction method for aggregation operators that may be used in assessing output of scientists. We show that the most often currently used indices of bibliometric impact, like Hirsch's h, Woeginger's w, Egghe's g, Kosmulski's MAXPROD, and similar constructions, may be obtained by means of our framework. Moreover, the model easily leads to some new, very interesting functions.
stringi is THE R package for correct, fast, and simple string processing in each locale and native charset. Another alpha release (for testing purposes) can be automatically downloaded by calling in R:
source('http://stringi.rexamine.com/install.R') # Message from the future: the link is outdated
The auto-installer gives access to a Windows i386/x64 build for R 3.0 or allows building the package from sources on Linux or MacOS.
UPDATE@2013-11-13. Version 0.1-10 now available.
Includes some bugfixes. Moreover, on Linux/UNIX
./configure now first
tries to read build settings from
(as the usage of
icu-config is deprecated).
UPDATE@2013-11-16. Version 0.1-11 now available.
ICU4C is now statically linked on Windows, so there is no need
to download any additional libraries – a binary version is
now available for R 2.15.X and 3.0.X. Moreover, on platforms where
packages are built from sources, the
now tries to find ICU4C automagically.
UPDATE@2013-11-21. Build of version 0.1-11 now available for OS X (x64) and R 3.0. Have fun.
UPDATE@2014-02-15. Version 0.1-20 (source and Win_build only) now available. Now it does not depend on any external ICU library (the library source code is included).
The alpha release (for testing purposes) is available here (includes Windows i386/x64 build for R 3.0). Any comments and suggestions are welcome!
Gagolewski M., Scientific Impact Assessment Cannot be Fair, Journal of Informetrics 7(4), 2013, pp. 792-802.
Abstract: In this paper we deal with the problem of aggregating numeric sequences of arbitrary length that represent e.g. citation records of scientists. Impact functions are the aggregation operators that express as a single number not only the quality of individual publications, but also their author's productivity.
We examine some fundamental properties of these aggregation tools. It turns out that each impact function which always gives indisputable valuations must necessarily be trivial. Moreover, it is shown that for any set of citation records in which none is dominated by the other, we may construct an impact function that gives any a priori-established authors' ordering. Theoretically then, there is considerable room for manipulation in the hands of decision makers.
We also discuss the differences between the impact function-based and the multicriteria decision making-based approach to scientific quality management, and study how the introduction of new properties of impact functions affects the assessment process. We argue that simple mathematical tools like the h- or g-index (as well asother bibliometric impact indices) may not necessarily be a good choice when it comes to assess scientific achievements.