Selected article for: "model forecast and time series"

Author: Cherrie, Mark P. C.; Nichols, Gordon; Iacono, Gianni Lo; Sarran, Christophe; Hajat, Shakoor; Fleming, Lora E.
Title: Pathogen seasonality and links with weather in England and Wales: a big data time series analysis
  • Document date: 2018_8_28
  • ID: 0x4zrfw3_12
    Snippet: Supplementary to the time series analysis, an Rshiny app was developed to display the results and aid future hypothesis generation. The user can filter the pathogens by seasonality, prevalence and serotype. Once an individual serotype is selected, a range of descriptive information is available: Wikipedia description, total number of cases, time series plot, month plot of crude rate per 100,000 (England and Wales population), decomposition of tim.....
    Document: Supplementary to the time series analysis, an Rshiny app was developed to display the results and aid future hypothesis generation. The user can filter the pathogens by seasonality, prevalence and serotype. Once an individual serotype is selected, a range of descriptive information is available: Wikipedia description, total number of cases, time series plot, month plot of crude rate per 100,000 (England and Wales population), decomposition of time series, TBATS model forecast and weather scatterplot.

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