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We investigate the asymptotic behavior of several variants of the scan statistic applied to empirical distributions, which can be applied to detect the presence of an anomalous interval with any length. Of particular interest is Studentized…

Statistics Theory · Mathematics 2020-03-26 Andrew Ying , Wen-Xin Zhou

Prediction of events is the challenge in many different disciplines, from meteorology to finance; the more this task is difficult, the more a system is {\it complex}. Nevertheless, even according to this restricted definition, a general…

chao-dyn · Physics 2007-05-23 Maurizio Serva

The incorporation of systematic uncertainties into confidence interval calculations has been addressed recently in a paper by Conrad et al. (Physical Review D 67 (2003) 012002). In their work, systematic uncertainities in detector…

Data Analysis, Statistics and Probability · Physics 2009-11-10 Gary C. Hill

We address the question how citation-based bibliometric indicators can best be normalized to ensure fair comparisons between publications from different scientific fields and different years. In a systematic large-scale empirical analysis,…

Digital Libraries · Computer Science 2013-04-03 Ludo Waltman , Nees Jan van Eck

The Leiden Ranking 2011/2012 provides the Proportion top-10% publications (PP top 10%) as a new indicator. This indicator allows for testing the difference between two ranks for statistical significance.

Computers and Society · Computer Science 2011-12-20 Loet Leydesdorff , Lutz Bornmann

We introduce a new unsupervised anomaly detection ensemble called SPI which can harness privileged information - data available only for training examples but not for (future) test examples. Our ideas build on the Learning Using Privileged…

Machine Learning · Computer Science 2018-05-25 Shubhranshu Shekhar , Leman Akoglu

The most frequently used indicators for the productivity and impact of scientists are the total number of publication ($N_{pub}$), total number of citations ($N_{cit}$) and the Hirsch (h) index. Since the seminal paper of Hirsch, in 2005,…

Digital Libraries · Computer Science 2023-04-26 Tamás Biró , András Telcs , Mété Józsa , Zoltán Néda

This paper serves a twofold purpose. First, a unified perspective on diversity indices is introduced based on an entropic basis. It is shown that the class of all linear combinations of the entropic basis, referred to as the class of linear…

Statistics Theory · Mathematics 2020-01-22 Zhiyi Zhang , Michael Grabchak

Entropy measures of probability distributions are widely used measures in ecology, biology, genetics, and in other fields, to quantify species diversity of a community. Unfortunately, entropy-based diversity indices, or diversity indices…

Populations and Evolution · Quantitative Biology 2014-08-14 Karim T. Abou-Moustafa

Sample overlap is a common issue in evidence synthesis in the field of medical research, particularly when integrating findings from observational studies utilizing existing databases such as registries. Due to the general inaccessibility…

Methodology · Statistics 2026-02-26 Zhentian Zhang , Tim Friede , Tim Mathes

In this paper we review the socalled altmetrics or alternative metrics. This concept raises from the development of new indicators based on Web 2.0, for the evaluation of the research and academic activity. The basic assumption is that…

Digital Libraries · Computer Science 2013-06-28 Daniel Torres-Salinas , Alvaro Cabezas-Clavijo , Evaristo Jimenez-Contreras

Progress in science and technology is punctuated by disruptive innovation and breakthroughs. Researchers have characterized these disruptions to explore the factors that spark such innovations and to assess their long-term trends. However,…

Social and Information Networks · Computer Science 2025-02-25 Munjung Kim , Sadamori Kojaku , Yong-Yeol Ahn

Researchers often misinterpret and misrepresent statistical outputs. This abuse has led to a large literature on modification or replacement of testing thresholds and $P$-values with confidence intervals, Bayes factors, and other devices.…

Methodology · Statistics 2020-10-02 Zad Rafi , Sander Greenland

The ongoing growth in the volume of scientific literature available today precludes researchers from efficiently discerning the relevant from irrelevant content. Researchers are constantly interested in impactful papers, authors and venues…

Digital Libraries · Computer Science 2015-08-11 Neil Shah , Yang Song

We have developed a (freeware) routine for "referenced publication years spectroscopy" (RPYS) and apply this method to the historiography of "iMetrics," that is, the junction of the journals Scientometrics, Informetrics, and the relevant…

Digital Libraries · Computer Science 2013-11-22 Loet Leydesdorff , Lutz Bornmann , Werner Marx , Staša Milojević

One of the major problems for maximum likelihood estimation in the well-established directional models is that the normalising constants can be difficult to evaluate. A new general method of "score matching estimation" is presented here on…

Statistics Theory · Mathematics 2016-04-29 Kanti V Mardia , John T Kent , Arnab K Laha

The tension between qualitative theorizing and quantitative methods is pervasive in the social sciences, and poses a constant challenge to empirical research. But in science studies as an interdisciplinary specialty, there are additional…

Digital Libraries · Computer Science 2015-05-25 Loet Leydesdorff

Bibliometric methods are used in multiple fields for a variety of purposes, namely for research evaluation. Most bibliometric analyses have in common their data sources: Thomson Reuters' Web of Science (WoS) and Elsevier's Scopus. This…

Digital Libraries · Computer Science 2015-11-26 Philippe Mongeon , Adele Paul-Hus

The quality of supernova data will dramatically increase in the next few years by new experiments that will add high-redshift supernova to the currently known ones. In order to use this new data to discriminate between different dark energy…

Astrophysics · Physics 2015-06-24 Emille E. O. Ishida

We revisit the classical problem of estimating an unknown distribution from its samples by fitting a mixture model that minimizes cross-entropy loss. Framing the task as a stochastic convex optimization problem over the space of $ M…

Machine Learning · Statistics 2026-05-26 Mohammadreza Ahmadypour , Tara Javidi , Farinaz Koushanfar
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