Abstract. The property of monotonicity, which requires a function to preserve a given order, has been considered the standard in the aggregation of real numbers for decades. In this paper, we argue that, for the case of multidimensional data, an order-based definition of monotonicity is far too restrictive. We propose several meaningful alternatives to this property not involving the preservation of a given order by returning to its early origins stemming from the field of calculus. Numerous aggregation methods for multidimensional data commonly used by practitioners are studied within our new framework.
Abstract. In the field of information fusion, the problem of data aggregation has been formalized as an order-preserving process that builds upon the property of monotonicity. However, fields such as computational statistics, data analysis and geometry, usually emphasize the role of equivariances to various geometrical transformations in aggregation processes. Admittedly, if we consider a unidimensional data fusion task, both requirements are often compatible with each other. Nevertheless, in this paper we show that, in the multidimensional setting, the only idempotent functions that are monotone and orthogonal equivariant are the over-simplistic weighted centroids. Even more, this result still holds after replacing monotonicity and orthogonal equivariance by the weaker property of orthomonotonicity. This implies that the aforementioned approaches to the aggregation of multidimensional data are irreconcilable, and that, if a weighted centroid is to be avoided, we must choose between monotonicity and a desirable behaviour with regard to orthogonal transformations.
Abstract. On the grounds of the revealed, mutual resemblance between the behaviour of users of Stack Exchange and the dynamics of the citations accumulation process in the scientific community, we tackled an outwardly intractable problem of assessing the impact of introducing "negative" citations.
Although the most frequent reason to cite a paper is to highlight the connection between the two publications, researchers sometimes mention an earlier work to cast a negative light. While computing citation-based scores, for instance the h-index, information about the reason why a paper was mentioned is neglected. Therefore it can be questioned whether these indices describe scientific achievements accurately.
In this contribution we shed insight into the problem of "negative" citations, analysing data from Stack Exchange and, to draw more universal conclusions, we derive an approximation of citations scores. Here we show that the quantified influence of introducing negative citations is of lesser importance and that they could be used as an indicator of where attention of scientific community is allocated.
stringibrings significant improvements in the way substring extraction tasks are performed.
Change-log since v1.3.1:
* [NEW FEATURE] #30: New function `stri_sub_all()` - a version of `stri_sub()` accepting list `from`/`to`/`length` arguments for extracting multiple substrings from each string in a character vector. * [NEW FEATURE] #30: New function `stri_sub_all<-()` (and its `%<%`-friendly version, `stri_sub_replace_all()`) - for replacing multiple substrings with corresponding replacement strings. * [NEW FEATURE] In `stri_sub_replace()`, `value` parameter has a new alias, `replacement`. * [NEW FEATURE] New convenience functions based on `stri_remove_empty()`: `stri_omit_empty_na()`, `stri_remove_empty_na()`, `stri_omit_empty()`, and also `stri_remove_na()`, `stri_omit_na()`. * [BUGFIX] #343: `stri_trans_char()` did not yield correct results for overlapping pattern and replacement strings. * [WARNFIX] #205: `configure.ac` is now included in the source bundle.
agopis now available on CRAN. See below for more details.
0.2-2 /2019-03-05/ * [IMPORTANT CHANGE] All functions dealing with binary relations now are named like `rel_*`. Moreover, `de_transitive()` has been renamed `rel_reduction_hasse()`. * [IMPORTANT CHANGE] The definition of `owa()`, `owmax()`, and `owmin()` is now consistent with that of (Grabisch et al., 2009), i.e., uses nondecreasing vectors, and not nonincreasing ones. * [NEW FUNCTIONS] `rel_closure_reflexive()`, `rel_reduction_reflexive()`, `rel_is_symmetric()`, `rel_closure_symmetric()`, `rel_is_irreflexive()`, `rel_is_asymmetric()`, `rel_is_antisymmetric()`, `rel_is_cyclic()`, etc., modify given adjacency matrices representing binary relations over finite sets. * [NEW FUNCTIONS] some predefined fuzzy logic connectives have been added, e.g. ,`tnorm_minimum()`, `tnorm_drastic()`, `tnorm_product()`, `tnorm_lukasiewicz()`, `tnorm_fodor()`, `tconorm_minimum()`, `tconorm_drastic()`, `tconorm_product()`, `tconorm_lukasiewicz()`, `tconorm_fodor()`, `fnegation_classic()`, `fnegation_minimal()`, `fnegation_maximal()`, `fnegation_yager()`, `fimplication_minimal()`, `fimplication_maximal()`, `fimplication_kleene()`, `fimplication_lukasiewicz()`, `fimplication_reichenbach()`, `fimplication_fodor()`, `fimplication_goguen()`, `fimplication_goedel()`, `fimplication_rescher()`, `fimplication_weber()`, `fimplication_yager()`. * [NEW FUNCTION] `check_comonotonicity()` determines if two vectors are comonotonic. * [NEW FUNCTIONS] `pord_spread()`, `pord_spreadsym()`, `pord_nd()` - example preorders on sets of vectors. * [NEW FEATURE] `plot_producer()` gained a new argument: `a`. * [BUGFIX] `rel_closure_transitive()` - a resulting matrix was not necessarily transitive. * [BUGFIX] `prepare_arg_numeric_sorted` (internal, C++) did not sort some vectors. * [BUGFIX] All built-in aggregation functions now throw an error on empty vectors. * [INFO] The package no longer depends on the `Matrix` package. The `igraph` package is only suggested. * [INFO] Most of the functions are now implemented in C++.
Abstract. The problem of penalty-based data aggregation in generic real normed vector spaces is studied. Some existence and uniqueness results are indicated. Moreover, various properties of the aggregation functions are considered.
stringi(one of the most often downloaded extensions on CRAN) is available. Check out the change-log for more information.
* [BACKWARD INCOMPATIBILITY] #335: A fix to #314 (by design) prevented the use of the system ICU if the library had been compiled with `U_CHARSET_IS_UTF8=1`. However, this is the default setting in `libicu`>=61. From now on, in such cases the system ICU is used more eagerly, but `stri_enc_set()` issues a warning stating that the default (UTF-8) encoding cannot be changed. * [NEW FEATURE] #232: All `stri_detect_*` functions now have the `max_count` argument that allows for, e.g., stopping at first pattern occurrence. * [NEW FEATURE] #338: `stri_sub_replace()` is now an alias for `stri_sub<-()` which makes it much more easily pipable (@yutannihilation, @BastienFR). * [NEW FEATURE] #334: Added missing `icudt61b.dat` to support big-endian platforms (thanks to Dimitri John Ledkov @xnox). * [BUGFIX] #296: Out-of-the box build used to fail on CentOS 6, upgraded `./configure` to `--disable-cxx11` more eagerly at an early stage. * [BUGFIX] #341: Fixed possible buffer overflows when calling `strncpy()` from within ICU 61. * [BUGFIX] #325: Made `./configure` more portable so that it works under `/bin/dash` now. * [BUGFIX] #319: Fixed overflow in `stri_rand_shuffle()`. * [BUGFIX] #337: Empty search patters in search functions (e.g., `stri_split_regex()` and `stri_count_fixed()`) used to raise too many warnings on empty search patters.
Abstract. The problem of the piecewise linear approximation of fuzzy numbers giving outputs nearest to the inputs with respect to the Euclidean metric is discussed. The results given in Coroianu et al. (Fuzzy Sets Syst 233:26–51, 2013) for the 1-knot fuzzy numbers are generalized for arbitrary n-knot (n>=2) piecewise linear fuzzy numbers. Some results on the existence and properties of the approximation operator are proved. Then, the stability of some fuzzy number characteristics under approximation as the number of knots tends to infinity is considered. Finally, a simulation study concerning the computer implementations of arithmetic operations on fuzzy numbers is provided. Suggested concepts are illustrated by examples and algorithms ready for the practical use. This way, we throw a bridge between theory and applications as the latter ones are so desired in real-world problems.