Iterated filtering algorithms are a tool for maximum likelihood inference on partially observed dynamical systems. Stochastic perturbations to theâ€¦Â (More)

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2017

2017

- Dao Nguyen, Edward L. Ionides
- Statistics and Computing
- 2017

Simulation-based inference for partially observed stochastic dynamic models is currently receiving much attention due to the factâ€¦Â (More)

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2017

2017

Infectious disease surveillance data often provides only partial information about the progression of the disease in theâ€¦Â (More)

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2016

2016

- Bingbo Cui, Haoqian Huang, Xiyuan Chen
- 2016 IEEE Chinese Guidance, Navigation andâ€¦
- 2016

An iterated filtering method is presented to improve the update stage of nonlinear filtering. First, we develop a generalizedâ€¦Â (More)

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Review

2015

Review

2015

- Andrew S Azman, Francisco J Luquero, Iza Ciglenecki, Rebecca F Grais, David A Sack, Justin Lessler
- 2015

Country-wide data from the 2008-2009 cholera epidemic in Zimbabwe came from the authors of Reyburn et al.4 Country-level data wasâ€¦Â (More)

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2014

2014

- Wan Yang, Alicia Karspeck, Jeffrey Shaman
- PLoS Computational Biology
- 2014

A variety of filtering methods enable the recursive estimation of system state variables and inference of model parameters. Theseâ€¦Â (More)

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2014

2014

This paper investigates the adaptive sensing for cooperative target tracking in threedimensional environments by multipleâ€¦Â (More)

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2012

2012

- Jie Cheng, Tom Brown, Ming-Chi Hsu
- 2012

In this project we propose a mixed graphical model that allows us to model data sets with both continuous and discrete variablesâ€¦Â (More)

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2010

2010

1. Partially-observed Markov processes 1 2. A first example: a discrete-time bivariate autoregressive process. 3 3. Defining aâ€¦Â (More)

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2010

2010

- Stefan HÃ¤gnesten, Jimmy Olsson
- 2010

In this note we apply the particle-based iterated filtering algorithm proposed by Ionides et al. (2009) to the problem ofâ€¦Â (More)

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2009

2009

Inference for partially observed Markov process models has been a longstanding methodological challenge with many scientific andâ€¦Â (More)

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