Zobrazeno 1 - 10
of 68
pro vyhledávání: '"Konstantinos Fokianos"'
Publikováno v:
Data Science in Science, Vol 3, Iss 1 (2024)
We study the problem of modeling and inference for spatio-temporal count processes. Our approach uses parsimonious parameterisations of multivariate autoregressive count time series models, including possible regression on covariates. We control the
Externí odkaz:
https://doaj.org/article/7f266bb8f70648fca82e703f600c2a25
Autor:
Theodoros Moysiadis, Dimitris Koparanis, Konstantinos Liapis, Maria Ganopoulou, George Vrachiolias, Ioannis Katakis, Chronis Moyssiadis, Ioannis S. Vizirianakis, Lefteris Angelis, Konstantinos Fokianos, Ioannis Kotsianidis
Publikováno v:
iScience, Vol 26, Iss 9, Pp 107591- (2023)
Summary: Personalized prediction is ideal in chronic lymphocytic leukemia (CLL). Although refined models have been developed, stratifying patients in risk groups, it is required to accommodate time-dependent information of patients, to address the cl
Externí odkaz:
https://doaj.org/article/7c568fa0025644d8bb9ec3c3df02d576
Autor:
Maria Ganopoulou, Efstratios Kontopoulos, Konstantinos Fokianos, Dimitris Koparanis, Lefteris Angelis, Ioannis Kotsianidis, Theodoros Moysiadis
Publikováno v:
Algorithms, Vol 17, Iss 4, p 138 (2024)
Questionnaires on health-related quality of life (HRQoL) play a crucial role in managing patients by revealing insights into physical, psychological, lifestyle, and social factors affecting well-being. A methodological aspect that has not been adequa
Externí odkaz:
https://doaj.org/article/4641babc3043456a8903905fe6a2b76e
Autor:
Ilias Gountas, Annalisa Quattrocchi, Ioannis Mamais, Constantinos Tsioutis, Eirini Christaki, Konstantinos Fokianos, Georgios Nikolopoulos
Publikováno v:
BMC Public Health, Vol 21, Iss 1, Pp 1-8 (2021)
Abstract Background Cyprus addressed the first wave of SARS CoV-2 (COVID-19) by implementing non-pharmaceutical interventions (NPIs). The aims of this study were: a) to estimate epidemiological parameters of this wave including infection attack ratio
Externí odkaz:
https://doaj.org/article/fb8749abc79b4953b9eafa24643b9d38
Autor:
Sergios Agapiou, Andreas Anastasiou, Anastassia Baxevani, Christos Nicolaides, Georgios Hadjigeorgiou, Tasos Christofides, Elisavet Constantinou, Georgios Nikolopoulos, Konstantinos Fokianos
Publikováno v:
Scientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
Abstract We present different data analytic methodologies that have been applied in order to understand the evolution of the first wave of the Coronavirus disease 2019 in the Republic of Cyprus and the effect of different intervention measures that h
Externí odkaz:
https://doaj.org/article/6f82bd749a1440d887075332777f6e99
Publikováno v:
Journal of Statistical Software, Vol 82, Iss 1, Pp 1-51 (2017)
The R package tscount provides likelihood-based estimation methods for analysis and modeling of count time series following generalized linear models. This is a flexible class of models which can describe serial correlation in a parsimonious way. The
Externí odkaz:
https://doaj.org/article/b116a033f11f45dc95d75660129ed2a9
Publikováno v:
Austrian Journal of Statistics, Vol 43, Iss 3 (2014)
We discuss the analysis of count time series following generalised linear models in the presence of outliers and intervention effects. Different modifications of such models are formulated which allow to incorporate, detect and to a certain degree di
Externí odkaz:
https://doaj.org/article/ce65208e3f7c45668335976a7f4d3dc8
Publikováno v:
Armillotta, M, Fokianos, K & Krikidis, I 2023, Bootstrapping Network Autoregressive Models for Testing Linearity . in Studies in Computational Intelligence . Studies in Computational Intelligence, vol. 1084, Springer Science and Business Media Deutschland GmbH, pp. 99-116 . https://doi.org/10.1007/978-3-031-24453-7_6
Studies in Computational Intelligence, 99-116
STARTPAGE=99;ENDPAGE=116;TITLE=Studies in Computational Intelligence
Studies in Computational Intelligence ISBN: 9783031244520
Studies in Computational Intelligence, 99-116
STARTPAGE=99;ENDPAGE=116;TITLE=Studies in Computational Intelligence
Studies in Computational Intelligence ISBN: 9783031244520
We develop methodology for network data with special attention to epidemic network spatio-temporal structures. We provide estimation methodology for linear network autoregressive models for both continuous and count multivariate time series. A study
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c3ef2b36e686a17b2198f2f13f7d1463
https://research.vu.nl/en/publications/23908c1d-3800-4b1f-8c2d-540ec0fb5f0e
https://research.vu.nl/en/publications/23908c1d-3800-4b1f-8c2d-540ec0fb5f0e
A novel methodology is proposed for clustering multivariate time series data using energy distance defined in Sz\'ekely and Rizzo (2013). Specifically, a dissimilarity matrix is formed using the energy distance statistic to measure separation between
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7b42e0c43021a495d41ad896fd7de664
Publikováno v:
Armillotta, M, Tsagris, M & Fokianos, K 2022 ' The R-package PNAR for modelling count network time series ' arXiv.org . < https://arxiv.org/pdf/2211.02582.pdf >
Vrije Universiteit Amsterdam
Vrije Universiteit Amsterdam
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::abf714636bffce5e5a70e1df124a2214
https://research.vu.nl/en/publications/eef9b537-b258-42be-84fd-41e703576753
https://research.vu.nl/en/publications/eef9b537-b258-42be-84fd-41e703576753