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R Packages
htmldf(2021). Simple scraping and tidy webpage summaries.inspectdf(2021). Tools for Exploring and Comparing Data Frames. Seepkgdownsite for examples.tdf(2020). R Package: Tour de France winners and stages data.badlm(2020). R Package: Bayesian adaptive distributed lag models. v0.0.0.9000.smnet(2020). Smoothing for Stream Network Data.CARBayesST(2019). Spatio-Temporal Generalised Linear Mixed Models for Areal Unit Data.inspectpd(2019). Python package. Tools for Exploring and Comparing Data Frames.
Selected presentations
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Newcastle Upon Tyne Data Science Meetup, March 2021. Exploring Exploratory Data Analysis
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Strathclyde University, Royal Statistical Society, Glasgow local group meeting, December 2017. So we're all data scientists now?
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EdinbR, Edinburgh R Users group, June 2017. Doing machine learning in R.
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Joint Statistical Meeting, Chicago, August 2016. Adaptive distributed lag models.
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Basque Centre for Applied Mathematics seminar, Bilbao, Spain, November 2015. Challenges in the statistical modelling of data on large river networks.
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Joint Statistical Meeting, Seattle, August 2015. Challenges in modelling air pollution and understanding its impact on human health.
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Conference of the International Environmetrics Society, Anchorage, Alaska, June 2013. Assessing and comparing the performance of models for stream network data.
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Lancaster University, Royal Statistical Society, Lancashire local group meeting, April 2012. (with Prof. Adrian Bowman). Going with the flow: flexible regression for river networks.
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26th International Workshop on Statistical Modelling, Valencia, July 2011. Distributed lag models for hydrological data.
Published Papers
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Lee, D., Rushworth, A., Napier, G. (2018). Spatio-temporal areal unit modelling in R with conditional autoregressive priors using the CARBayesST package. Journal of Statistical Software. 84 (9).
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Rushworth, AM., Lee, D., Sarran, C. (2017). An adaptive spatiotemporal smoothing model for estimating trends and step changes in disease risk. Journal of the Royal Statistical Society: Series C (Applied Statistics). 66 (1), 141-157.
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Lee, D., Mukhopadhyay, S., Rushworth, A., Sahu, SK. (2016). A rigorous statistical framework for spatio-temporal pollution prediction and estimation of its long-term impact on health. Biostatistics 18 (2), 370-385.
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Rushworth, AM., Peterson, EE., Ver Hoef, JM., Bowman, AW. (2015). Validation and comparison of geostatistical and spline models for spatial stream networks. Environmetrics. 26 (5), 327-338.
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Rushworth, A., Lee, D., Mitchell, R. (2014). A spatio-temporal model for estimating the long-term effects of air pollution on respiratory hospital admissions in Greater London. Spatial and spatio-temporal epidemiology. 10, 29-38.
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Lee, D., Rushworth, A., Sahu, SK. (2014). A Bayesian localized conditional autoregressive model for estimating the health effects of air pollution. Biometrics. 70 (2), 419-429.
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O'Donnell, D., Rushworth, A., Bowman, AW., Scott, EM., Hallard, M. (2014). Flexible regression models over river networks. Journal of the Royal Statistical Society: Series C (Applied Statistics). 63 (1), 47-63.
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Rushworth, AM., Bowman, AW., Brewer, MJ., SJ Langan. (2013). Distributed lag models for hydrological data. Biometrics 69 (2), 537-544.
Unpublished articles
- Rushworth, A. (2018). Bayesian Distributed Lag Models. arXiv preprint arXiv:1801.06670.