Using Extreme Value Theory Approaches to Forecast the Probability of Outbreak of Highly Pathogenic Influenza in Zhejiang, China
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DOI: 10.1371/journal.pone.0118521
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References listed on IDEAS
- Eui-Ki Kim & Jong Hyeon Seok & Jang Seok Oh & Hyong Woo Lee & Kyung Hyun Kim, 2013. "Use of Hangeul Twitter to Track and Predict Human Influenza Infection," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-11, July.
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Cited by:
- Maud Thomas & Holger Rootzén, 2022. "Real‐time prediction of severe influenza epidemics using extreme value statistics," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 71(2), pages 376-394, March.
- Bufalo, Michele & Ceci, Claudia & Orlando, Giuseppe, 2024. "Addressing the financial impact of natural disasters in the era of climate change," The North American Journal of Economics and Finance, Elsevier, vol. 73(C).
- Łuczak Aleksandra & Just Małgorzata, 2020. "The positional MEF-TOPSIS method for the assessment of complex economic phenomena in territorial units," Statistics in Transition New Series, Statistics Poland, vol. 21(2), pages 157-172, June.
- Aleksandra Łuczak & Małgorzata Just, 2020. "The positional MEF-TOPSIS method for the assessment of complex economic phenomena in territorial units," Statistics in Transition New Series, Polish Statistical Association, vol. 21(2), pages 157-172, June.
- Maud Thomas & Magali Lemaitre & Mark L Wilson & Cécile Viboud & Youri Yordanov & Hans Wackernagel & Fabrice Carrat, 2016. "Applications of Extreme Value Theory in Public Health," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-7, July.
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