Zobrazeno 1 - 10
of 210
pro vyhledávání: '"QA276"'
Autor:
Zhang, Jian
Publikováno v:
Statistics and Its Interface
The conventional beamformers that reconstruct the cerebral origin of brain activity measured outside the head via electro- and magnetoencephalography (EEG/MEG) suffer from depth bias and smearing of nearby sources. Here, to meet these methodological
Autor:
Eleni Matechou, Raffaele Argiento
We propose a novel approach for modelling capture-recapture (CR) data on open populations that exhibit temporary emigration, whilst also accounting for individual heterogeneity to allow for differences in visit patterns and capture probabilities betw
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::451f7ec9f07a0864ef3888de5694d4c4
https://kar.kent.ac.uk/96926/11/01621459.2022.pdf
https://kar.kent.ac.uk/96926/11/01621459.2022.pdf
Publikováno v:
Ecology and Evolution
Ecology and Evolution, Vol 11, Iss 3, Pp 1131-1149 (2021)
Ecology and Evolution, Vol 11, Iss 3, Pp 1131-1149 (2021)
Capture–recapture experiments are conducted to estimate population parameters such as population size, survival rates, and capture rates. Typically, individuals are captured and given unique tags, then recaptured over several time periods with the
Autor:
Katsarakis, Stylianos
The current thesis consists of two results obtained during my PhD, both related to approximations of high/infinite-dimensional measures emerging from the Bayesian approach to inverse problems. In the first part, we study a technique for the reduction
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=core_ac_uk__::ee69b2ec235127e5eaaf44d243db1084
Autor:
Calder, P
In this thesis we derive and apply influence functions for the detection of observations in multivariate analysis which when omitted from, or added to, the data lead to substantial changes in some aspect of our analysis. Emphasis is placed on the inf
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=core_ac_uk__::302aef332bff312cf598bbd8b6449451
https://kar.kent.ac.uk/86258/1/375052.pdf
https://kar.kent.ac.uk/86258/1/375052.pdf
Autor:
Gitanjali M. Singh, Majid Ezzati, Gretchen A Stevens, Alan D. Dangour, Mariachiara Di Cesare, Rosemary Green, James E. Bennett, Farshad Farzadfar, James Bentham, Goodarz Danaei, John K Lin
Publikováno v:
Nature Food
Nat Food
Nat Food
Food systems are increasingly globalized and interdependent, and diets around the world are changing. Characterization of national food supplies and how they have changed can inform food policies that ensure national food security, support access to
Autor:
Qian, Wendi
Bayesian methods for group sequential clinical trials have received increasing attention recently. They offer an approach for dealing with many difficult problems and have some practical advantages over frequentist methods. This thesis covers Bayes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8ee7a70210494b3c77523951bc049120
Autor:
Campbell, Edward
The robustness of certain model-fitting procedures, based on statistical transforms, is investigated using the Influence Function. Our discussion is in two parts. In the first, we focus on estimateing the parameters of particular distributions, given
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::49d06d3727eb96ffa8b6e77def909f38
https://kar.kent.ac.uk/86151/1/315178.pdf
https://kar.kent.ac.uk/86151/1/315178.pdf
Over the last 10 to 15 years, active inference has helped to explain various brain mechanisms from habit formation to dopaminergic discharge and even modelling curiosity. However, the current implementations suffer from an exponential (space and time
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::24dfa3a9af27eb1878421f083a9034f0
http://arxiv.org/abs/2111.11107
http://arxiv.org/abs/2111.11107
Publikováno v:
Proceedings of the Future Technologies Conference (FTC) 2021, Volume 1 ISBN: 9783030899059
Many interesting problems in statistics and machine learning can be written as \(min_xF(x)=f(x)+g(x)\), where \(x\) is the model parameter, \(f\) is the loss and \(g\) is the regularizer. Examples include regularized regression in high-dimensional fe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f37fbccba0627709d8947d255c9b9114
https://kar.kent.ac.uk/78761/1/FTC_2021_Nonsmooth.pdf
https://kar.kent.ac.uk/78761/1/FTC_2021_Nonsmooth.pdf