Zobrazeno 1 - 10
of 83
pro vyhledávání: '"Fellows, Ian E."'
Autor:
Fellows, Ian E., Hladik, Wolfgang, Eaton, Jeffrey W., Voetsch, Andrew C., Parekh, Bharat S., Shiraishi, Ray W.
Estimating HIV-1 incidence using biomarker assays in cross-sectional surveys is important for understanding the HIV pandemic. However, the utility of these estimates has been limited by uncertainty about what input parameters to use for False Recency
Externí odkaz:
http://arxiv.org/abs/2204.00048
Publikováno v:
In Social Networks July 2024 78:81-91
Background: The impact of individual non-pharmaceutical interventions (NPI) such as state-wide stay-at-home orders, school closures and gathering size limitations, on the COVID-19 epidemic is unknown. Understanding the impact that above listed NPI ha
Externí odkaz:
http://arxiv.org/abs/2007.12644
Autor:
Cloete, Allanise *, Mabaso, Musawenkosi, Savva, Helen, van der Merwe, L Leigh-Ann, Naidoo, Dhee, Petersen, Zaino, Kose, Zamakayise, Mthembu, Jacqueline, Moyo, Sizulu, Skinner, Donald, Jooste, Sean, Fellows, Ian E, Shiraishi, Ray W, Mwandingi, Shaalula L, Simbayi, Leickness C
Publikováno v:
In The Lancet HIV June 2023 10(6):e375-e384
Autor:
Fellows, Ian E.
Full probability models are critical for the statistical modeling of complex networks, and yet there are few general, flexible and widely applicable generative methods. We propose a new family of probability models motivated by the idea of network gr
Externí odkaz:
http://arxiv.org/abs/1804.04583
Autor:
Fellows, Ian E.
Experimental testing is vital in the optimization of web applications, and as such A/B testing has been widely adopted as a methodology for determining optimal content for many web applications. While some testing platforms provide sequentially valid
Externí odkaz:
http://arxiv.org/abs/1710.01285
Akademický článek
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Autor:
Fellows, Ian E
Contrastive divergence (CD) is a promising method of inference in high dimensional distributions with intractable normalizing constants, however, the theoretical foundations justifying its use are somewhat shaky. This document proposes a framework fo
Externí odkaz:
http://arxiv.org/abs/1405.0602
Autor:
Fellows, Ian E., Handcock, Mark S.
Exponential-family random network (ERN) models specify a joint representation of both the dyads of a network and nodal characteristics. This class of models allow the nodal characteristics to be modelled as stochastic processes, expanding the range a
Externí odkaz:
http://arxiv.org/abs/1303.1219
Autor:
Fellows, Ian E (AUTHOR) ian@fellstat.com
Publikováno v:
Journal of Survey Statistics & Methodology. Apr2022, Vol. 10 Issue 2, p377-396. 20p.