Zobrazeno 1 - 10
of 241
pro vyhledávání: '"Markatou Marianthi"'
The safety of medical products continues to be a significant health concern worldwide. Spontaneous reporting systems (SRS) and pharmacovigilance databases are essential tools for postmarketing surveillance of medical products. Various SRS are employe
Externí odkaz:
http://arxiv.org/abs/2410.01168
In the statistical literature, as well as in artificial intelligence and machine learning, measures of discrepancy between two probability distributions are largely used to develop measures of goodness-of-fit. We concentrate on quadratic distances, w
Externí odkaz:
http://arxiv.org/abs/2407.16374
We introduce the QuadratiK package that incorporates innovative data analysis methodologies. The presented software, implemented in both R and Python, offers a comprehensive set of goodness-of-fit tests and clustering techniques using kernel-based qu
Externí odkaz:
http://arxiv.org/abs/2402.02290
We present an index of dependence that allows one to measure the joint or mutual dependence of a $d$-dimensional random vector with $d>2$. The index is based on a $d$-dimensional Kendall process. We further propose a standardized version of our index
Externí odkaz:
http://arxiv.org/abs/2011.12268
The Kendall plot ($\K$-plot) is a plot measuring dependence between the components of a bivariate random variable. The $\K$-plot graphs the Kendall distribution function against the distribution function of $VU$, where $V$ and $U$ are independent uni
Externí odkaz:
http://arxiv.org/abs/1811.08836
Autor:
Golzy, Mojgan, Markatou, Marianthi
Many applications of interest involve data that can be analyzed as unit vectors on a d-dimensional sphere. Specific examples include text mining, in particular clustering of documents, biology, astronomy and medicine among others. Previous work has p
Externí odkaz:
http://arxiv.org/abs/1803.04485
Autor:
Talal, Andrew H., Markatou, Marianthi, Sofikitou, Elisavet M., Brown, Lawrence S., Perumalswami, Ponni, Dinani, Amreen, Tobin, Jonathan N.
Publikováno v:
In Contemporary Clinical Trials January 2022 112
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Akademický článek
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Publikováno v:
New Advances in Statistics and Data Science 2017, 27-44
A scientific phenomenon under study may often be manifested by data arising from processes, i.e. sources, that may describe this phenomenon. In this contex of multi-source data, we define the "out-of-source" error, that is the error committed when a
Externí odkaz:
http://arxiv.org/abs/1612.07670