Zobrazeno 1 - 10
of 128
pro vyhledávání: '"Heckman, Nancy"'
Autor:
Sidrow, Evan, Heckman, Nancy, McRae, Tess M., Volpov, Beth L., Trites, Andrew W., Fortune, Sarah M. E., Auger-Méthé, Marie
Ecologists often use a hidden Markov model to decode a latent process, such as a sequence of an animal's behaviours, from an observed biologging time series. Modern technological devices such as video recorders and drones now allow researchers to dir
Externí odkaz:
http://arxiv.org/abs/2409.18091
Autor:
Sidrow, Evan, Heckman, Nancy, Bouchard-Côté, Alexandre, Fortune, Sarah M. E., Trites, Andrew W., Auger-Méthé, Marie
Hidden Markov models (HMMs) are popular models to identify a finite number of latent states from sequential data. However, fitting them to large data sets can be computationally demanding because most likelihood maximization techniques require iterat
Externí odkaz:
http://arxiv.org/abs/2310.04620
Educational resources, such as web apps and self-directed tutorials, have become popular tools for teaching and active learning. Ideally, students - the intended users of these resources - should be involved in the resource development stage. However
Externí odkaz:
http://arxiv.org/abs/2304.00149
Autor:
Sidrow, Evan, Heckman, Nancy, Fortune, Sarah M. E., Trites, Andrew W., Murphy, Ian, Auger-Méthé, Marie
Publikováno v:
Can J Statistics 50 (2022) 327-356
Data sets comprised of sequences of curves sampled at high frequencies in time are increasingly common in practice, but they can exhibit complicated dependence structures that cannot be modelled using common methods of Functional Data Analysis (FDA).
Externí odkaz:
http://arxiv.org/abs/2101.03268
Building on recent work in statistical science, the paper presents a theory for modelling natural phenomena that unifies physical and statistical paradigms based on the underlying principle that a model must be nondimensionalizable. After all, such p
Externí odkaz:
http://arxiv.org/abs/2002.11259
Akademický článek
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Autor:
Fu, Eric, Heckman, Nancy
Functional data often exhibit both amplitude and phase variation around a common base shape, with phase variation represented by a so called warping function. The process removing phase variation by curve alignment and inference of the warping functi
Externí odkaz:
http://arxiv.org/abs/1712.07265
Akademický článek
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Publikováno v:
The Canadian Journal of Statistics 2017
We develop and apply an approach for analyzing multi-curve data where each curve is driven by a latent state process. The state at any particular point determines a smooth function, forcing the individual curve to switch from one function to another.
Externí odkaz:
http://arxiv.org/abs/1504.02813
Analysis of Aggregated Functional Data from Mixed Populations with Application to Energy Consumption
Publikováno v:
Environmetrics 2016
Understanding the energy consumption patterns of different types of consumers is essential in any planning of energy distribution. However, obtaining consumption information for single individuals is often either not possible or too expensive. Theref
Externí odkaz:
http://arxiv.org/abs/1402.1740