Klaus Ackermann, Simon D. Angus, Paul A. Raschky
arXiv 16 Oct 2020 · Statistics — Applications
arXiv:2010.08102 · PDF · DOI · OpenAlex · Extracted main text
Alternative data is increasingly adapted to predict human and economic behaviour. This paper introduces a new type of alternative data by re-conceptualising the internet as a data-driven insights platform at global scale. Using data from a unique internet activity and location dataset drawn from over 1.5 trillion observations of end-user internet connections, we construct a functional dataset covering over 1,600 cities during a 7 year period with temporal resolution of just 15min. To predict accurate temporal patterns of sleep and work activity from this data-set, we develop a new technique, Segmented Functional Classification Analysis (SFCA), and compare its performance to a wide array of linear, functional, and classification methods. To confirm the wider applicability of SFCA, in a second application we predict sleep and work activity using SFCA from US city-wide electricity demand functional data. Across both problems, SFCA is shown to out-perform current methods.
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The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.
| Reference | Intensity | Mentions | Sections | Main text | |
|---|---|---|---|---|---|
| 1 | An, N., W. Zhao, J. Wang, D. Shang, and E. Zhao (2013, January) (2013) Using multi-output feedforward neural network with empirical mode decomposition based signal filtering for electricity demand fo… | 0.644 | 2 | 2 | 100% |
| 2 | Bogomolov, A., B. Lepri, R. Larcher, F. Antonelli, F. Pianesi, and A… (2016) Energy consumption prediction using people dynamics derived from cellular network data | 0.644 | 2 | 2 | 100% |
| 3 | Cabrera, B. L. and F. Schulz (2017, March) (2017) Forecasting Generalized Quantiles of Electricity Demand: A Functional Data Approach | 0.644 | 2 | 2 | 100% |
| 4 | Hyndman, R. J. and S. Fan (2010, April) (2010) Density Forecasting for Long-Term Peak Electricity Demand | 0.644 | 2 | 2 | 100% |
| 5 | Muratori, M., M. C. Roberts, R. Sioshansi, V. Marano, and G. Rizzoni… (2013) A highly resolved modeling technique to simulate residential power demand | 0.644 | 2 | 2 | 100% |
| 6 | Reiss, P. T. and R. T. Ogden (2007, September) (2007) Functional Principal Component Regression and Functional Partial Least Squares | 0.644 | 2 | 2 | 100% |
| 7 | Yao, F., H.-G. Müller, and J.-L. Wang (2005, December) (2005) Functional linear regression analysis for longitudinal data | 0.644 | 2 | 2 | 100% |
| Heidemann | unmatched citation key Heidemann | 0.585 | 3 | 1 | 100% |
| Shang | unmatched citation key Shang | 0.585 | 3 | 1 | 100% |
| Tibshirani | unmatched citation key Tibshirani | 0.585 | 3 | 1 | 100% |
Showing the top 10 of 158 scored citations. 3 of these could not be matched to a bibliography entry, so only the citation key is shown.