Publications

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2013
El-Ayouti, A., and H. Abou-Ali, "Spatial Heterogeneity of the Nile Water Quality in Egypt", Journal of Environmental Statistics, vol. 4, issue 8, 2013.
2014
Abou-Ali, H., and A. El-Ayouti, "Nile water pollution and technical efficiency of crop production in Egypt: an assessment using spatial and non-parametric modelling", Journal of Environmental and Ecological Statistics, vol. 21, issue 2, pp. 221-238, 2014.
2015
Elayouty, A., M. Scott, C. Miller, S. Waldron, and M. Franco-Villoria, "Challenges in modeling detailed and complex environmental data sets: a case study modeling the excess partial pressure of fluvial CO2", Journal of Environmental and Ecological Statistics, vol. 23, issue 1, pp. 65–87, 2015.
2017
Elayouty, A., M. Scott, and C. Miller, "Discussion of “Should we sample a time series more frequently? Decision support via multirate spectrum estimation” by Nason, Powell, Elliott and Smith", Journal of the Royal Statistical Society: Series A (Statistics in Society), vol. 180, no. 2, pp. 353-407, 2017. AbstractWebsite

Summary Suppose that we have a historical time series with samples taken at a slow rate, e.g. quarterly. The paper proposes a new method to answer the question: is it worth sampling the series at a faster rate, e.g. monthly? Our contention is that classical time series methods are designed to analyse a series at a single and given sampling rate with the consequence that analysts are not often encouraged to think carefully about what an appropriate sampling rate might be. To answer the sampling rate question we propose a novel Bayesian method that incorporates the historical series, cost information and small amounts of pilot data sampled at the faster rate. The heart of our method is a new Bayesian spectral estimation technique that is capable of coherently using data sampled at multiple rates and is demonstrated to have superior practical performance compared with alternatives. Additionally, we introduce a method for hindcasting historical data at the faster rate. A freeware R package, regspec, is available that implements our methods. We illustrate our work by using official statistics time series including the UK consumer price index and counts of UK residents travelling abroad, but our methods are general and apply to any situation where time series data are collected.

2020
Elayouty, A., M. Scott, and C. Miller, "Discussion of ``Functional models for time-varying random objects" by Paromita Dubey and Hans-Georg Muller", Journal of the Royal Statistical Society, Series B, vol. 82, issue 2, pp. 275-327, 2020.
Elayouty, A., "Variograms for Functional Data", Wiley StatsRef: Statistics Reference Online: John Wiley & Sons, 2020.
2022
Elayouty, A., M. Scott, and C. Miller, "Time-varying functional principal components for non-stationary EpCO2 in freshwater systems", Journal of Agricultural, Biological, and Environmental Statistics, vol. 27, issue 3, pp. 506-522, 2022.
2023
Elayouty, A., and H. Abou-Ali, "Functional data analysis of the relationship between electricity consumption and climate change drivers", Journal of Applied Statistics, vol. 50, issue 10, pp. 2267–2285, 2023.