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Journal of Applied Statistics|August 2, 2023
Classification and severity progression measure of COVID-19 patients using pairs of multi-omic factorsTeng Chen, Paweł Polak, Stanislav UryasevJournal of Applied Statistics|August 2, 2023
Statistical modelling of COVID-19 pandemic development applying branching processesD Atanasov, Vessela Stoimenova, Nikolay M YanevJournal of Applied Statistics|August 2, 2023
Time fused coefficient SIR model with application to COVID-19 epidemic in the United StatesHou-Cheng Yang, Yishu Xue, Yuqing Pan, et al.Journal of Applied Statistics|August 2, 2023
Identification of factors impacting on the transmission and mortality of COVID-19Peiyi Zhang, Tianning Dong, Ninghui Li, et al.Journal of Applied Statistics|July 12, 2023
The fraud loss for selecting the model complexity in fraud detectionSimon Boge Brant, Ingrid Hobæk HaffJournal of Applied Statistics|July 12, 2023
The relationship between moderate to vigorous physical activity and metabolic syndrome: a Bayesian measurement error approachDaniel Ries, Alicia CarriquiryJournal of Applied Statistics|July 12, 2023
A double generally weighted moving average control chart for monitoring the process variabilityVasileios Alevizakos, Kashinath Chatterjee, Christos Koukouvinos, et al.Journal of Applied Statistics|July 12, 2023
Functional data analysis of the relationship between electricity consumption and climate change driversA Elayouty, H Abou-AliJournal of Applied Statistics|July 31, 2026
DeepVARwT: deep learning for a VAR model with trendXixi Li, Jingsong YuanJournal of Applied Statistics|June 16, 2022
Accurate estimation for extra-Poisson variability assuming random effect modelsRicardo Puziol de Oliveira, Jorge Alberto AchcarPageof 123