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Earo Wang
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Cited by
Year
Package ‘hts’
RJ Hyndman, A Lee, E Wang, S Wickramasuriya, ME Wang
9482021
Large-scale unusual time series detection
RJ Hyndman, E Wang, N Laptev
2015 IEEE international conference on data mining workshop (ICDMW), 1616-1619, 2015
1692015
forecast: Forecasting functions for time series and linear models. R package version 8.4
R Hyndman, G Athanasopoulos, C Bergmeir, G Caceres, L Chhay, ...
URL: https://CRAN. R-project. org/package= forecast, 2018
155*2018
Fast computation of reconciled forecasts for hierarchical and grouped time series
RJ Hyndman, AJ Lee, E Wang
Computational statistics & data analysis 97, 16-32, 2016
1252016
tsfeatures: Time series feature extraction
R Hyndman, Y Kang, P Montero-Manso, T Talagala, E Wang, Y Yang, ...
R package version 1 (0), 2019
59*2019
A new tidy data structure to support exploration and modeling of temporal data
E Wang, D Cook, RJ Hyndman
Journal of Computational and graphical Statistics 29 (3), 466-478, 2020
222020
Fable: Forecasting models for tidy time series
M O’Hara-Wild, R Hyndman, E Wang
R package version 0.2 1, 2020
212020
Calendar-based graphics for visualizing people’s daily schedules
E Wang, D Cook, RJ Hyndman
Journal of Computational and Graphical Statistics 29 (3), 490-502, 2020
82020
The state‐of‐the‐art on tours for dynamic visualization of high‐dimensional data
S Lee, D Cook, N da Silva, U Laa, N Spyrison, E Wang, HS Zhang
Wiley Interdisciplinary Reviews: Computational Statistics, e1573, 2021
2*2021
Package ‘feasts’
M O'Hara-Wild, R Hyndman, E Wang, D Cook, T Talagala, L Chhay, ...
12019
Conversations in Time: Interactive Visualization to Explore Structured Temporal Data.
E Wang, D Cook
R Journal 13 (1), 2021
2021
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Articles 1–11