** FuzzyNumbers Package NEWS **
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0.4-1 /2015-02-26/
* added possibility and necessity functions that represent comparison
operators <=,<,>,>= (with tests and description in vignette)
* added functions to determine minimum and maximum of two fuzzy numbers
(description in vignette)
* added operator ^ for calculation of integer power of
PiecewiseLinearFuzzyNumber
* added function arctan2 for calculation of atan2 with
PiecewiseLinearFuzzyNumber arguments
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0.3-5 /2014-10-01/
* added proper import directives in NAMESPACE
* piecewiseLinearApproximation: method="ApproximateNearestEuclidean"
no longer accepted; use "NearestEuclidean" instead.
* package vignette now in the vignettes/ directory.
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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.
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0.3-1 /2013-06-23/
* piecewiseLinearApproximation() - general case (any knot.n)
for method="NearestEuclidean" now available.
Thus, method="ApproximateNearestEuclidean" is now deprecated.
* New binary arithmetic operators, especially
for PiecewiseLinearFuzzyNumbers: +, -, *, /
* New method: fapply() - applies a function on a PLFN
using the extension principle
* New methods: as.character(); also used by show().
This function also allows to generate LaTeX code defining the FN
(toLaTeX arg thanks to Jan Caha).
* as.FuzzyNumber(), as.TriangularFuzzyNumber(), as.PowerFuzzyNumber(), and
as.PiecewiseLinearFuzzyNumber() are now S4 methods,
and can be called on objects of type numeric, as well as on
various FNs
* piecewiseLinearApproximation() and as.PiecewiseLinearFuzzyNumber()
argument `knot.alpha` now defaults to equally distributed knots
(via given `knot.n`). If `knot.n` is missing, then it is guessed
from `knot.alpha`.
* PiecewiseLinearFuzzyNumber() now accepts missing `a1`, `a2`, `a3`, `a4`,
and `knot.left`, `knot.right` of length `knot.n`+2. Moreover, if `knot.n`
is not given, then it is guessed from length(knot.left).
If `knot.alpha` is missing, then the knots will be equally distributed
on the interval [0,1].
* alphacut() now always returns a named two-column matrix.
evaluate() returns a named vector.
* New function: TriangularFuzzyNumber - returns a TrapezoidalFuzzyNumber.
* Function renamed: convert.side to convertSide, convert.alpha
to convertAlpha, approx.invert to approxInvert
* Added a call to setGeneric("plot", function(x, y, ...) ...
to avoid a warning on install
* The FuzzyNumbers Tutorial has been properly included
as the package's vignette
* DiscontinuousFuzzyNumber class has been marked as **EXPERIMENTAL**
in the manual
* Man pages extensively updated
* FuzzyNumbers devel repo moved to GitHub
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0.2-1 /2012-12-27/
* approx.invert(): a new function to find the numerical
inverse of a given side/alpha-cut generating function
(by default via Hermite monotonic spline interpolation)
* convert.side(), convert.alpha():
new functions to convert sides and alpha cuts
to side generating funs and alpha cut generators
* FuzzyNumber class validity check for lower, upper, left, right:
* checks whether each function is properly vectorized
and gives numeric results
* does not check for the number of formal arguments,
but just uses the first from the list
* Suggests `testthat`
* Each object has been documented
* First CRAN release
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0.1-1 /2012-07-01/
* Initial release
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